online courses - freeCodeCamp.org

1000+ Free Developer Certifications

freeCodeCamp — Mon, 13 Jan 2025 06:00:00 +0000

By Dhawal Shah

Did you know that organizations such as freeCodeCamp, Google, and Harvard offer online courses to help you learn software development? And that many of these include free certificates and badges?

To help you choose one that's right for you, I've created a full list.

As avid online learners, my Class Central colleagues and I have completed hundreds of online courses over the years, including many with free certificates, as you can see in the collage below.

In 2025, free certificates have become rarer. But if you know where to look, there is still an abundance of free certificates available online for learning software development.

Some of the free certificates earned by the Class Central team.

As you likely know, freeCodeCamp offers free certifications. But so do big tech companies and institutions such as Google, Microsoft, and Harvard.

In this article, we bring together all the free certificates and badges that are scattered across the web. In total, the platforms below offer over 900 free certificate courses for learning software development.

I (Dhawal) started Class Central back in 2011, when universities such as Stanford began to offer some of their courses online for free. Since then, the Class Central database has grown to over 250K online courses.

Having written about online education for over a decade, I remember when platforms like Coursera and edX offered free certificates. Then, rather abruptly, free certificates seemed to pretty much disappear.

This inspired us to write a Massive List of Free Certificates and Badges. To our surprise, we discovered there were still thousands of free certificates available online. To date, that article has received 10M views.

In the same vein, this article aims to draw attention to the organizations that continue to support open education in software development by offering free certificate courses. These include:

Learning platforms — e.g. LinkedIn Learning, CodeSignal, and freeCodeCamp
Leading universities — e.g. Harvard and the University of Helsinki
Big tech companies — e.g. Google and IBM.

Please note, Class Central is not involved in running the courses or issuing certificates. This is a dynamic field and you may discover that a course you choose is no longer available, or doesn’t have a free certificate any more. We recommend you always check before starting a course.

freeCodeCamp Free Certifications

Archisha's freeCodeCamp free certificate

freeCodeCamp platform offers thousands of hours of learning content, broken down into certifications on subjects such as web development and data science.

Here are the certifications currently offered, several others are due to be released soon:

While strictly not developer courses, A2 English for Developers and B1 English for Developers focuses on vocabulary that is particularly useful for developers. Prepare for real-world interactions by applying English skills in professional and technical settings.

Cisco Free Badges

Cisco Network Academy

Cisco, the IT and networking giant, offers a series of self-paced online courses through its Networking Academy platform; some include free badges for skills learned. Here’s a selection:

You can find the full list of Cisco Networking Academy courses here.

CodeSignal Free Certificates

Pat's free CodeSignal certificate

CodeSignal is a growing platform that offers 2000+ courses and learning paths with free certificates in coding, AI & ML, data science, interview prep, and more. As well as developer and IT certificates, CodeSignal teaches valuable soft skills.

Here’s a selection:

You can find more details in our dedicated article, and the full list of CodeSignal Learn courses.

Google Free Certificates and Badges

Pat’s free Google badge

Google has launched several initiatives to teach people skills such as coding, digital marketing, and data analytics. Some offer certificates, some have badges.

Here is a selection of Google’s offerings:

You can find more details in our dedicated article and here is a complete list of courses by Google.

HackerRank Free Certificates

Manoel’s HackerRank free certificate

HackerRank is a platform for learning algorithms and data structures and preparing for coding interviews, provides skills certifications tests in topics such as problem solving, Python, and JavaScript.

Here are some of the 24 tests you may complete to earn a certificate:

Harvard Free Certificates

Pat’s Free Harvard CS50 Scratch Certificate

Harvard offers a series of academic online courses exploring various facets of computer science, including programming fundamentals and AI.

Here are Harvard’s current free certificate offerings. Remember that while you need an account with edX to submit the assignments, the free certificate comes directly from CS50.

You can find more details and how to receive your free certificate in our dedicated article and here is a complete list of courses from Harvard.

Hasso Plattner Institute Free Certificates

Hasso Plattner Institute free courses

The Hasso Plattner Institute offers a range of self-paced courses with free certificates of participation and achievement. Most courses are in German, but some are in English.

Here’s a selection of courses in English:

Hugging Face Free Certificates

Hugging Face courses

Hugging Face develops computation tools for building applications using machine learning and offers several courses, some with free certificates.

IBM Free Certificates and Badges

The CognitiveClass.ai homepage

IBM’s platform CognitiveClass.ai offers 100+ courses and 10 learning paths in data science, AI, big data, cloud computing, and blockchain. Some courses offer a completion badge or certificate. Check on the Cognitive Class.AI course page for details.

The platform also provides a virtual lab environment allowing users to practice what they’ve learned in the courses.

Here’s a selection:

Pat’s free certificate and badge for Introduction to IBM Storage and Cloud

Some of the 24 free learning paths and 582 free courses from IBM Training have free certificates and badges available from IBM Training or via Credly. Courses are in a range of fields including AI, automation, infrastructure, cloud, security, and more.

Kaggle Free Certificates

Kaggle free certificate courses

Kaggle is an online community for data scientists and aspiring data scientists alike. It offers over 50K public datasets, allowing you to build your own data science projects through Jupyter notebooks, and participate in competitions.

In addition, the platform offers a series of courses to learn the fundamentals of data science. Each leads to a certificate of completion.

LinkedIn Learning Courses with Free Certificates

Suparn’s LinkedIn Learning free certificate

LinkedIn Learning, the online learning platform integrated with the LinkedIn professional social network, offers more than a hundred online courses and learning paths that include a free certificate.

Here’s a selection of LinkedIn Learning free certificate courses:

You can find more details and the full list or free certificates in our dedicated article, and here is a complete list of courses by LinkedIn Learning.

MATLAB Free Certificates

MATLAB free courses

MathWorks, the company behind the MATLAB programming language and software, offers 23 free online courses with certificates through their MATLAB Academy platform.

The courses introduce learners to the MATLAB language and tools — with a focus on machine learning — and MathWorks’ specialized software, such as Simulink. You can find all the details and how to receive your free certificate in our dedicated article.

Here’s a selection:

Semrush Academy Free Certificates

Semrush Academy free courses

Although Semrush is primarily a business and marketing specialist, some of their free certificate courses are relevant for developers and IT professionals:

University of Helsinki Free Certificates

Pat’s Elements of AI free certificate

The University of Helsinki offers academic online courses through its independent course platform, MOOC.fi, including the following courses which include a free certificate of completion:

upGrad Free Certificates

Suparn’s upGrad free certificate

upGrad is an online learning platform that offers free programs and courses on subjects such as data science, business analytics, and technology.

An e-Certificate of Completion is provided in 30 days after you successfully finish all the modules within your program. Your phone number is required while registering a course so you may receive calls and messages from upGrad.

Here are some of the free programs offered on upGrad:

FutureLearn Free Certificates

Elham’s FutureLearn free certificate

FutureLearn, the European counterpart to Coursera and edX, offers some courses that include a free “digital upgrade” — which, among others, entails a free certificate of completion.

Here’s a list of some of FutureLearn’s free offerings:

You can find more details in our dedicated article and here is a full list of FutureLearn courses.

Wolfram U Free Certificates

Wolfram U free courses

The Wolfram Language is a powerful programming tool employed in science, engineering, data science, and finance. It combines math, data analysis, and general programming, and forms the core of Wolfram’s popular software, Mathematica. You can find all the details in our dedicated article.

Here is a selection of Wolfram U’s 40+ free certificate courses:

More Free Certificates

If you don’t find what you need here, browse Class Central’s catalog of 250K courses or visit our thematic collections:

You can find all our free certificates articles here.

120 Free Online Math Courses from the World’s Top Universities

Manoel — Sun, 12 Jan 2025 06:00:00 +0000

In this article, we’ve compiled over 300 online courses offered by the 60 best universities in the world for studying math.

We did so by combining popular university rankings to identify the best institutions, and then using the Class Central database to find all their math online courses.

Methodology

I built the list following the same data-driven approach used to build the list of computer science courses from the top CS universities.

First, I identified the leading world university rankings. Since I was specifically interested in math, I looked at their latest rankings of the best universities for studying math (or closest superset). Here are the rankings I ended up using:

Then, we crawled and scraped each ranking.

Now that I had some data, I used Jupyter with Python to process it. I combined the three rankings into one by averaging the position of each university in each ranking. Then, I filtered out the universities that didn’t offer online courses, and limited the list to the top 60 institutions.

For the latest update of this article, Suparn used the same sources and methodology to find the top 60 universities offering online math courses.

Combined ranking: top 10 universities for studying mathematics in 2024

As you can see in the image above, I found that the top three math institutions are:

Finally, we used the Class Central database, with its 250K online courses, to find all the math courses offered by the universities in the ranking.

The end result is a list of more than 300 online courses offered by 60 best universities in the world for studying math in 2025.

While processing the data, I noticed something interesting: 59 of the top 60 universities offer online courses, a lot more than I would have guessed. The world’s top institutions are very prolific creators of online courses.

Stats

Enrollments range from 21 to over 13 million. There are 8 courses with over 1 million enrollments
Altogether, the courses in this list have over 52 million enrollments, with an average of over 296 thousand enrollments
222 courses are free and 98 are paid
291 courses are in English, 19 Chinese, 7 French, and 1 each in Spanish, German, Korean.
Together, they account for 2,118 reviews at Class Central, with an average of 28 reviews
Average Rating 4.51 out of 5.0
80 courses are beginner level, 57 are intermediate level, and 11 are advanced level.

General Mathematics (45)

Fibonacci Numbers and the Golden Ratio from The Hong Kong University of Science and Technology ★★★★★(271)
How to Learn Math: For Students from Stanford University ★★★★☆(17)
Convex Optimization from Stanford University ★★★★★(8)
Mathematics for Engineers: The Capstone Course from The Hong Kong University of Science and Technology ★★★★★(5)
A-level Mathematics for Year 12 - Course 1: Algebraic Methods, Graphs and Applied Mathematics Methods from Imperial College London ★★★★★(2)
Mathematical Thinking in Computer Science from University of California, San Diego ★★★★★(2)
Engineering Mathematics from University of Washington ★★★★★(1)
Mathematics for Engineers from The Hong Kong University of Science and Technology ★★★★★(1)
Political Geometry - The Mathematics of Redistricting from Harvard University ★★★★★(1)
Essential Math for AI from Columbia University
A-level Further Mathematics for Year 12 - Course 1: Complex Numbers, Matrices, Roots of Polynomial Equations and Vectors from Imperial College London
Delivery Problem from University of California, San Diego
A-level Further Mathematics for Year 13 - Course 1: Differential Equations, Further Integration, Curve Sketching, Complex Numbers, the Vector Product and Further Matrices from Imperial College London
Cómo Aprender Matemáticas - Para Estudiantes from Stanford University
Further Mathematics Year 13 course 2: Applications of Differential Equations, Momentum, Work, Energy & Power, The Poisson Distribution, The Central Limit Theorem, Chi Squared Tests, Type I and II Errors from Imperial College London
Foundational Mathematics for AI from Johns Hopkins University
Introduction to Complexity Science from Nanyang Technological University
Introduction to optimization on smooth manifolds: first order methods from École Polytechnique Fédérale de Lausanne
Nonlinear Dynamics and Chaos from Cornell University
Mathematics of Big Data and Machine Learning, IAP 2020 from Massachusetts Institute of Technology
How Learning Ten Equations Can Improve Your Life - David Sumpter from University of Oxford
离散数学 from Shanghai Jiao Tong University
The Mathematics of Visual Illusions - Ian Stewart from University of Oxford
Math Boot Camp for Engineers from Massachusetts Institute of Technology
Wrinkling - Oxford Mathematics Research Seminar from University of Oxford
Analyse I (partie 4) : Limite d'une fonction, fonctions continues from École Polytechnique Fédérale de Lausanne
Analyse I (partie 5) : Fonctions continues et fonctions dérivables, la fonction dérivée from École Polytechnique Fédérale de Lausanne
The Potential for AI in Science and Mathematics from University of Oxford
Stanford Lecture - Pi and The Art of Computer Programming - 2019 from Stanford University
Analyse I (partie 6) : Etudes des fonctions, développements limités from École Polytechnique Fédérale de Lausanne
Prime Time - James Maynard from University of Oxford
Bach and the Cosmos from University of Oxford
Analyse I (partie 1) : Prélude, notions de base, les nombres réels from École Polytechnique Fédérale de Lausanne
Analyse I (partie 7) : Intégrales indéfinies et définies, intégration (chapitres choisis) from École Polytechnique Fédérale de Lausanne
The Number Mysteries - Marcus du Sautoy from University of Oxford
Analyse I (partie 2) : Introduction aux nombres complexes from École Polytechnique Fédérale de Lausanne
Analyse I (partie 3) : Suites de nombres réels I et II from École Polytechnique Fédérale de Lausanne
Introduction to Metric Spaces from Massachusetts Institute of Technology
Cascading Principles - Conrad Shawcross, Martin Bridson and James Sparks with Fatos Ustek from University of Oxford
Why Does Rudolph Have a Shiny Nose? - Chris Budd from University of Oxford
Blueprints - How Mathematics Shapes Creativity from University of Oxford
Théorie des Groupes (partie 1) - Une introduction à la théorie des catégories from École Polytechnique Fédérale de Lausanne
Productive Generalization - Timothy Gowers from University of Oxford
Euler’s Pioneering Equation from University of Oxford
The Travelling Santa Problem and Other Seasonal Challenges - Marcus du Sautoy from University of Oxford

Linear Algebra (32)

Matrix Algebra for Engineers from The Hong Kong University of Science and Technology ★★★★★(843)
Linear Algebra - Foundations to Frontiers from The University of Texas at Austin ★★★★☆(15)
Introduction to Linear Models and Matrix Algebra from Harvard University ★★★★☆(12)
Mathematics for Machine Learning: Linear Algebra from Imperial College London ★★★☆☆(9)
Linear Algebra from Massachusetts Institute of Technology ★★★★★(5)
Matrix Methods in Data Analysis, Signal Processing, and Machine Learning from Massachusetts Institute of Technology ★★★★★(3)
Algèbre Linéaire (Partie 1) from École Polytechnique Fédérale de Lausanne ★★★★★(2)
MIT - A 2020 Vision of Linear Algebra, Spring 2020 from Massachusetts Institute of Technology ★★★★★(2)
Algèbre Linéaire (Partie 2) from École Polytechnique Fédérale de Lausanne ★★★★★(1)
Algèbre Linéaire (Partie 3) from École Polytechnique Fédérale de Lausanne ★★★★★(1)
Linear Algebra III: Determinants and Eigenvalues from Georgia Institute of Technology ★★★★★(1)
Linear Algebra IV: Orthogonality & Symmetric Matrices and the SVD from Georgia Institute of Technology ★★★★★(1)
Applications of Linear Algebra from Georgia Institute of Technology ★★★★★(1)
Linear Algebra: Linear Systems and Matrix Equations from Johns Hopkins University
Linear Algebra II: Matrix Algebra from Georgia Institute of Technology
Linear Algebra: Matrix Algebra, Determinants, & Eigenvectors from Johns Hopkins University
Linear Algebra I: Linear Equations from Georgia Institute of Technology
Math for AI beginner part 1 Linear Algebra from Korea Advanced Institute of Science and Technology
Introduction to Linear Algebra from The University of Sydney
Linear Algebra: Orthogonality and Diagonalization from Johns Hopkins University
Advanced Linear Algebra: Foundations to Frontiers from The University of Texas at Austin
Engineering Mathematics: Linear Algebra and ODEs, Fall 2014 from Massachusetts Institute of Technology
Linear Algebra from Elementary to Advanced from Johns Hopkins University
Introductory Linear Algebra from Georgia Institute of Technology
Linear Algebra from Massachusetts Institute of Technology
Matrix Calculus for Machine Learning and Beyond from Massachusetts Institute of Technology
A Vision of Linear Algebra from Massachusetts Institute of Technology
Computational Science and Engineering I from Massachusetts Institute of Technology
Linear Algebra and NxN Systems from Massachusetts Institute of Technology
线性代数(1) from Tsinghua University
线性代数(2) from Tsinghua University
简明线性代数 from Tsinghua University

Differential Equations (12)

Differential Equations for Engineers from The Hong Kong University of Science and Technology ★★★★★(374)
Differential Equations Part I Basic Theory from Korea Advanced Institute of Science and Technology ★★★★★(2)
Differential Equations from Massachusetts Institute of Technology ★★★★★(2)
Differential Equations Part II Series Solutions from Korea Advanced Institute of Science and Technology
Differential Equations Part III Systems of Equations from Korea Advanced Institute of Science and Technology
Engineering Math: Differential Equations and Linear Algebra from Massachusetts Institute of Technology
Numerical Solution of Differential Equations - Oxford Mathematics 3rd Year Student Lecture from University of Oxford
Differential Equations from Massachusetts Institute of Technology
Differential Equations: Fourier Series and Partial Differential Equations from Massachusetts Institute of Technology
Introduction to Differential Equations from Massachusetts Institute of Technology
Differential Equations: 2x2 Systems from Massachusetts Institute of Technology
A-level Further Mathematics for Year 13 - Course 1: Differential Equations, Further Integration, Curve Sketching, Complex Numbers, the Vector Product and Further Matrices from Imperial College London

Statistics & Probability (54)

Intro to Statistics from Stanford University ★★★★☆(39)
Probability - The Science of Uncertainty and Data from Massachusetts Institute of Technology ★★★★★(34)
Statistical Learning with R from Stanford University ★★★★☆(28)
Fundamentals of Statistics from Massachusetts Institute of Technology ★★★★☆(10)
Data Analysis: Basic Probability and Statistics from Harvard University ★★★★☆(6)
Introduction to Probability and Data with R from Duke University ★★★★☆(6)
Statistical Inference and Modeling for High-throughput Experiments from Harvard University ★★★★★(4)
Computational Probability and Inference from Massachusetts Institute of Technology ★★★★★(3)
Introduction to Statistics from Stanford University ★★★★★(2)
Statistics: Unlocking the World of Data from University of Edinburgh ★★★★☆(2)
Introduction to Probability from Harvard University ★★★★★(1)
Introduction to Statistics & Data Analysis in Public Health from Imperial College London ★★★★★(1)
Summary Statistics in Public Health from Johns Hopkins University ★★★★★(1)
Hypothesis Testing in Public Health from Johns Hopkins University ★★★★★(1)
A Crash Course in Causality: Inferring Causal Effects from Observational Data from University of Pennsylvania ★★★★☆(1)
Introductory Statistics : Basic Ideas and Instruments for Statistical Inference from Seoul National University ★☆☆☆☆(1)
Statistics for Applications from Massachusetts Institute of Technology ★★★★★(1)
Causal Inference from Columbia University
Causal Inference 2 from Columbia University
Introductory Statistics : Analyzing Data Using Graphs and Statistics from Seoul National University
Survival Analysis in R for Public Health from Imperial College London
Statistics for Data Science Essentials from University of Pennsylvania
Logistic Regression in R for Public Health from Imperial College London
Introduction to Probability Management from Stanford University
Statistics Using Python from University of Wisconsin–Madison
Probability and Statistics I: A Gentle Introduction to Probability from Georgia Institute of Technology
Introductory Statistics : Sample Survey and Instruments for Statistical Inference from Seoul National University
Probability and Statistics III: A Gentle Introduction to Statistics from Georgia Institute of Technology
Inferential Statistics from Duke University
Statistics 110 - Probability from Harvard University
Mathematical understanding of uncertainty from Seoul National University
Probability and Statistics II: Random Variables – Great Expectations to Bell Curves from Georgia Institute of Technology
Probability and Statistics IV: Confidence Intervals and Hypothesis Tests from Georgia Institute of Technology
What are the Chances? Probability and Uncertainty in Statistics from Johns Hopkins University
Advanced Statistics for Data Science from Johns Hopkins University
Advanced Probability and Statistical Methods from Johns Hopkins University
Probabilistic Systems Analysis and Applied Probability from Massachusetts Institute of Technology
Statistics with Python from University of Michigan
Statistics with Python Using NumPy, Pandas, and SciPy from University of Michigan
Probabilistic Graphical Models from Stanford University
Probabilistic Systems Analysis and Applied Probability from Massachusetts Institute of Technology
Selected Topics on Discrete Choice from École Polytechnique Fédérale de Lausanne
Bayesian Networks 3 - Maximum Likelihood - Stanford CS221: AI (Autumn 2019) from Stanford University
Bayesian Networks 1 - Inference - Stanford CS221: AI from Stanford University
Bayesian Networks 2 - Forward-Backward - Stanford CS221: AI from Stanford University
Statistics, Confidence Intervals and Hypothesis Tests from Georgia Institute of Technology
MIT RES.6-012 Introduction to Probability, Spring 2018 from Massachusetts Institute of Technology
Data Overload - Making Sense of Statistics in the News, Kristin Sainani from Stanford University
Probability/Random Variables from Georgia Institute of Technology
Dependent Stopping Times and Application to Credit Risk Theory - BQE Lecture Series from New York University (NYU)
Inferenzstatistik from Duke University
The Counting Project - How Data Built the Modern World from University of Oxford
R을 사용한 확률 및 데이터 소개 from Duke University
Statistical Methods for Computer Science from Johns Hopkins University

Calculus (30)

Calculus: Single Variable Part 1 - Functions from University of Pennsylvania ★★★★★(8)
Introduction to Calculus from The University of Sydney ★★★★★(6)
Calculus: Single Variable Part 2 - Differentiation from University of Pennsylvania ★★★★★(5)
Calculus for Engineers from The Hong Kong University of Science and Technology ★★★★★(5)
Calculus: Single Variable Part 3 - Integration from University of Pennsylvania ★★★★☆(4)
Calculus: Single Variable Part 4 - Applications from University of Pennsylvania ★★★★★(3)
Single Variable Calculus from Massachusetts Institute of Technology ★★★★★(3)
Calculus Applied! from Harvard University ★★★★★(2)
Combinatorial Mathematics | 组合数学 from Tsinghua University ★★★★☆(2)
Introductory Calculus - Oxford Mathematics 1st Year Student Lecture from University of Oxford ★★★★★(2)
Calculus through Data & Modeling: Differentiation Rules from Johns Hopkins University ★★★★☆(1)
Single Variable Calculus from University of Pennsylvania
Applied Calculus with Python from Johns Hopkins University
Calculus through Data & Modeling: Precalculus Review from Johns Hopkins University
Applied Math for Materials Science and Engineering from Korea Advanced Institute of Science and Technology
Calculus through Data & Modeling: Limits & Derivatives from Johns Hopkins University
A-Level Further Mathematics for Year 12 - Course 2: 3 x 3 Matrices, Mathematical Induction, Calculus Methods and Applications, Maclaurin Series, Complex Numbers and Polar Coordinates from Imperial College London
Calculus through Data & Modelling: Series and Integration from Johns Hopkins University
Calculus through Data & Modelling: Techniques of Integration from Johns Hopkins University
Calculus through Data & Modelling: Integration Applications from Johns Hopkins University
Calculus through Data & Modeling: Applying Differentiation from Johns Hopkins University
Introduction to Advanced Calculus from The University of Sydney
Calculus 1C: Coordinate Systems & Infinite Series from Massachusetts Institute of Technology
Calculus 1A: Differentiation from Massachusetts Institute of Technology
Calculus 1B: Integration from Massachusetts Institute of Technology
微积分（先修课） from Tsinghua University
A-Level Further Mathematics for Year 12 - Course 2: 3 x 3 Matrices, Mathematical Induction, Calculus Methods and Applications, Maclaurin Series, Complex Numbers and Polar Coordinates from Imperial College London
微积分——极限理论与一元函数 from Tsinghua University
微积分-1 from Tsinghua University
微积分-2 from Tsinghua University

Mathematical Modeling (9)

Modelling Ice Sheets - Oxford Mathematics Research Seminar from University of Oxford ★★★★★(4)
Infectious Disease Modeling in Practice from Johns Hopkins University
Scaling the Maths of Life from University of Oxford
How Do Mathematicians Model Infectious Disease Outbreaks? from University of Oxford
Mathematical Modelling in Biology - Neuronal Signalling from University of Oxford
Mathematical Modelling in Biology - Enzyme Kinetics and Perturbation Theory - Lecture 2 from University of Oxford
Responsible Modelling and the Ethics of Mathematics for Decision Support from University of Oxford
3 Minute Thesis Competition 2025 - Oxford Mathematics Postgraduate Research Presentations from University of Oxford
Going for Gold - The Mathematics of Sporting Glory from University of Oxford

Convex Optimization (17)

Convex Optimization I - Lecture 1 from Stanford University
Convex Optimization I - Lecture 3 from Stanford University
Convex Optimization I - Lecture 2 from Stanford University
Convex Optimization I - Lecture 8 from Stanford University
Convex Optimization I - Lecture 5 from Stanford University
Convex Optimization I - Lecture 4 from Stanford University
Convex Optimization I - Lecture 6 from Stanford University
Convex Optimization I - Lecture 7 from Stanford University
Convex Optimization I - Lecture 13 from Stanford University
Convex Optimization I - Lecture 16 from Stanford University
Convex Optimization I - Lecture 15 from Stanford University
Convex Optimization I - Lecture 10 from Stanford University
Convex Optimization I - Lecture 9 from Stanford University
Convex Optimization I - Lecture 12 from Stanford University
Convex Optimization I - Lecture 11 from Stanford University
Convex Optimization I - Lecture 17 from Stanford University
最优化理论与方法 from Nanjing University

Probability Theory (8)

概率论与数理统计 from Tsinghua University
Introduction to Probability from Massachusetts Institute of Technology
How to Put Uncertainty into Numbers - Understanding Chance, Luck and Ignorance from University of Oxford
Can We Truly Understand by Counting? Understanding Complex Physical Systems Through Mathematics from University of Oxford
Probability, Measure and Martingales - Let There Be Time: Filtrations and Stopping Times from University of Oxford
Martingales: Definition and First Properties - Probability, Measure and Martingales from University of Oxford
Probability, Measure and Martingales - Stopped Martingales and Optional Sampling Theorems from University of Oxford
Vitali's Convergence Theorem and Martingale Inequalities - Lecture 5 from University of Oxford

Others (113)

Vector Calculus for Engineers from The Hong Kong University of Science and Technology ★★★★★(261)
Introduction to Mathematical Thinking from Stanford University ★★★★☆(51)
Bayesian Statistics from Duke University ★★★☆☆(12)
Discovery Precalculus: A Creative and Connected Approach from The University of Texas at Austin ★★★★★(3)
Combinatorics and Probability from University of California, San Diego ★★★★☆(3)
Analytic Combinatorics from Princeton University ★★★★☆(3)
Data Science: Linear Regression from Harvard University ★★☆☆☆(3)
Engineering Calculus and Differential Equations from The University of Hong Kong ★★★★★(2)
Multivariable Calculus from Massachusetts Institute of Technology ★★★★★(2)
Introduction to Graph Theory from University of California, San Diego ★★★★★(2)
Linear Regression and Modeling from Duke University ★★★★☆(2)
Linear Regression in R for Public Health from Imperial College London ★★★★★(1)
Simple Regression Analysis in Public Health from Johns Hopkins University ★★★★★(1)
Precalculus from Modern States ★★★★★(1)
Algebra: Elementary to Advanced - Functions & Applications from Johns Hopkins University ★★★★☆(1)
Algebra: Elementary to Advanced from Johns Hopkins University ★★★★★(1)
Cours préparatoire: Fonctions Trigonométriques, Logarithmiques et Exponentielles from École Polytechnique Fédérale de Lausanne ★★★★☆(1)
The Banach Contraction Mapping Theorem - Oxford Mathematics 1st Year Lecture from University of Oxford ★★★★☆(1)
The Seduction of Curves - The Lines of Beauty That Connect Mathematics, Art and The Nude from University of Oxford ★★★★★(1)
Hamiltonian Paths in Antiquity - Stanford Lecture 2016 from Stanford University ★★★★★(1)
Precalculus: Relations and Functions from Johns Hopkins University
Precalculus: Mathematical Modeling from Johns Hopkins University
Precalculus: Periodic Functions from Johns Hopkins University
Precalculus through Data and Modelling from Johns Hopkins University
Combinatorics and Algorithms Design from Tsinghua University
组合数学 from Tsinghua University
Linear Regression Modeling for Health Data from University of Michigan
Differential Calculus through Data and Modeling from Johns Hopkins University
Differential Calculus from Massachusetts Institute of Technology
Graph Theory and Additive Combinatorics from Massachusetts Institute of Technology
Graph Theory and Additive Combinatorics from Massachusetts Institute of Technology
Petri网：模型、理论与应用 from Tsinghua University
Multivariable Calculus from Massachusetts Institute of Technology
Multivariable Calculus 1: Vectors and Derivatives from Massachusetts Institute of Technology
Multidimensional Analysis and Geometry - Introduction to the Derivative in Higher Dimensions - Lecture 1 from University of Oxford
Multivariable Calculus 3: Theorems and Applications from Massachusetts Institute of Technology
Multivariable Calculus 2: Integrals from Massachusetts Institute of Technology
微积分——多元函数与重积分 from Tsinghua University
多元微积分（先修课） from University of Science and Technology of China
Using Language Models to Understand Wage Premia from Stanford University
Algebra: Elementary to Advanced - Equations & Inequalities from Johns Hopkins University
Algebra: Elementary to Advanced - Polynomials and Roots from Johns Hopkins University
Honors Algebra 2: Linear and Quadratic Functions from Johns Hopkins University
History of Mathematics - Classical Algebra - 19th-Century Beginnings of Modern Algebra - 3rd Year Lecture from University of Oxford
History of Mathematics - Classical Algebra: Equation Solving 1800 BC - AD 1800 - 3rd Year Lecture from University of Oxford
Honors Algebra 2: Algebraic, Exponential & Log Functions from Johns Hopkins University
Honors Algebra 2 from Johns Hopkins University
Honors Algebra 2 from Johns Hopkins University
Honors Algebra 2: Series, Trigonometry, and Probability from Johns Hopkins University
Geometry - Scalar Triple Product: Oxford Mathematics First Year Student Lecture from University of Oxford
Introduction to Conic Sections and Their Mathematical Properties - Lecture 1 from University of Oxford
Natural Tilings: From Hard Rock to Soft Cells from University of Oxford
Calculus through Data & Modelling: Vector Calculus from Johns Hopkins University
Math for AI Beginner Part 2 : Vector Calulus from Korea Advanced Institute of Science and Technology
Multidimensional Analysis and Geometry: Introduction to the Derivative in Higher Dimensions - Lecture 2 from University of Oxford
Real Analysis from Massachusetts Institute of Technology
Real Analysis from Massachusetts Institute of Technology
Discrete Mathematics from Shanghai Jiao Tong University
离散数学概论 Discrete Mathematics Generality from Peking University
Mathematics for Computer Science from Massachusetts Institute of Technology
Data Science Decisions in Time: Using Causal Information from Johns Hopkins University
教育定量研究方法（高级） from Tsinghua University
Optimization: principles and algorithms - Linear optimization from École Polytechnique Fédérale de Lausanne
运筹学 from Tsinghua University
Meaningful Predictive Modeling from University of California, San Diego
Foundations of Probability and Random Variables from Johns Hopkins University
Stanford CS109 - Future of Probability - Lecture 28 from Stanford University
Probability, Measure and Martingales: An Introduction from University of Oxford
From Coin Flips to Clinical Trials - Introduction to Probability - Medical Software Course from Yale University
Introduction to Uncertainty Quantification from Johns Hopkins University
Random Processes from Johns Hopkins University
Algebraic Curves - Curves in Affine Plane and the Projective Plane - Lecture 3 from University of Oxford
Algebraic Curves - More on Projective Geometry - Lecture 2 from University of Oxford
Algebraic Curves - Properties of Algebraic Curves - Lecture 4 from University of Oxford
Numerical Methods Applied to Chemical Engineering from Massachusetts Institute of Technology
The Butterfly Effect - What Does It Really Signify? from University of Oxford
Integral Calculus through Data and Modeling from Johns Hopkins University
Foundations of Logic from Tsinghua University
Paradox and Infinity from Massachusetts Institute of Technology
Single Variable Calculus from Massachusetts Institute of Technology
Introduction to Functional Analysis from Massachusetts Institute of Technology
Groups and Group Actions - Representations of Groups by Permutations from University of Oxford
Théorie des Groupes (partie 2) - Quotients de groupe from École Polytechnique Fédérale de Lausanne
Théorie des Groupes (partie 3) - Actions de groupe from École Polytechnique Fédérale de Lausanne
Théorie des Groupes (partie 4) - Groupes abéliens et sous-groupes de Sylow from École Polytechnique Fédérale de Lausanne
Groups and Group Actions - Group Homomorphisms from University of Oxford
How to Be a Statistical Detective from Stanford University
Principles of Digital Communication II from Massachusetts Institute of Technology
Knotty Problems - Marc Lackenby from University of Oxford
Can Yule Solve My Problems - Alex Bellos from University of Oxford
Analysis III: Basic Properties of Riemann Integration - Lecture 1 from University of Oxford
Mathematical Methods for Engineers II from Massachusetts Institute of Technology
Why There Are No Three-Headed Monsters from University of Oxford
From Ronald Ross to ChatGPT: The Birth and Strange Life of the Random Walk from University of Oxford
Introduction to Complex Numbers - Lecture 1 from University of Oxford
A-level Further Mathematics for Year 12 - Course 1: Complex Numbers, Matrices, Roots of Polynomial Equations and Vectors from Imperial College London
Geometry: Conics - Lecture 2 from University of Oxford
Numbers Are Serious but They Are Also Fun - Michael Atiyah from University of Oxford
Linear Diophantine Equations and the Extended Euclidean Algorithm - Lecture 1 from University of Oxford
1 + 1 = 2 - The Foundation of Mathematical Counting and Number Systems from University of Oxford
Complex Analysis: Multivalued Functions and Integration - Lecture 4 from University of Oxford
Algebraic Topology - Algebraic Invariants of Spaces from University of Oxford
Algebraic Topology - Chains, Cycles, and Homology Classes from University of Oxford
Honors Algebra 2: Polynomials and Complex Numbers from Johns Hopkins University
Transfer Functions and the Laplace Transform from Massachusetts Institute of Technology
The Taylor Series, Complex Numbers, and Simple Harmonic Motion - Lecture 16 from Yale University
Social Sequence Analysis: An Introduction and Overview from The University of Chicago
数值分析与算法 from Tsinghua University
Lie Groups - Introduction to Lie Groups from University of Oxford
Lie Groups - The Exceptional Lie Group G2 from University of Oxford
Algebraic Curves - Introduction to Projective Geometry - Lecture 1 from University of Oxford
Commutative Algebra - Primary Decomposition from University of Oxford
Commutative Algebra - Primary Decomposition 2 from University of Oxford

More Courses

With over 300 courses to pick from, we hope you find something you like. But if these aren’t enough, check out Class Central’s catalog of 250K online courses or our thematic collections:

200+ Universities Just Launched 1000+ Free Online Courses. Here’s the Full List.

freeCodeCamp — Tue, 30 Jan 2024 09:00:00 +0000

By Dhawal Shah

If you haven’t heard, universities around the world are offering their courses online for free (or at least, partially free). These online courses are collectively called MOOCs or Massive Open Online Courses.

In the past ten years or so, over 1000 universities have created more than 20,000 such online courses. I’ve been keeping track of them this entire time here at Class Central, a search engine and reviews site for online education which has been used by 60 million learners around the world.

In the past six months alone, more than 200 universities — including Harvard, Stanford, MIT, and a few Ivy League Schools — have announced over 1000 such free online courses. I’ve compiled this list below and categorized the courses into the following subjects:

Computer Science (84)
Programming (54)
Science (99)
Engineering (88)
Business (150)
Personal Development (38)
Humanities (87)
Social Sciences (89)
Health & Medicine (91)
Education & Teaching (21)
Data Science (39)
Mathematics (32)
Art & Design (27)
International (130)

If the courses below don’t interest you, Class Central’s got you covered. Either browse our extensive catalog of 200,000 online courses or have a look at our thematic collections:

You can find all the Class Central free certificate articles here.

If you’re new to online education, have a look at our suggestions on how to learn online effectively.

Here’s the full list of new free online courses. Most of them are completely self-paced, so you can learn at your convenience.

Computer Science (81)

Herramientas de Inteligencia Artificial para la productividad. Más allá del ChatGPT from Universitat Politècnica de València ★★★★★(45)
Unlocking the Power of Generative AI with ChatGPT for Higher Education from Galileo University ★★★★★(7)
An Introduction to Logic for Computer Science from University of Leeds ★★★★★(1)
Machine Learning and AI with Python from Harvard University
[New] The AI Awakening: Implications for the Economy and Society from Stanford University
Introduction to Computational Science and Engineering from Massachusetts Institute of Technology
Generative AI Teach-Out from University of Michigan
Logistic Regression and Prediction for Health Data from University of Michigan
Generative AI Essentials: Overview and Impact from University of Michigan
Recommender Systems from Indian Institute of Technology, Kharagpur
Virtualization, Docker, and Kubernetes for Data Engineering from Duke University
[New] Operationalizing LLMs on Azure from Duke University
Basics of Computational Complexity from Indian Institute of Technology Kanpur
Assessment Design with AI from Georgia Institute of Technology
Chatbots for Instruction from Georgia Institute of Technology
AI for Teacher Assistance from Georgia Institute of Technology
Emerging Technology, Disruption, and AI from University of Illinois at Urbana-Champaign
Games and Information from NPTEL
AI in Marketing from Indian Institute of Technology Roorkee
AI Foundations: Prompt Engineering with ChatGPT from Arizona State University
Introduction to Machine Learning with Python from Arizona State University
Parallel Computer Architecture from Indian Institute of Technology Guwahati
An Introduction to Cryptography from University of Leeds
How to Get Into AI from University of Leeds
Introduction to Technology-Assisted Decision-Making from University of Leeds
How to Get Into Blockchain from University of Leeds
Edge Computing from Indian Institute of Technology Patna
Advanced topics in Wireless Communication (Hindi) from Indraprastha Institute of Information Technology Delhi
ChatGPT Advanced Data Analysis from Vanderbilt University
Innovative Teaching with ChatGPT from Vanderbilt University
Generative AI Primer from Vanderbilt University
Trustworthy Generative AI from Vanderbilt University
Generative AI for Leaders from Vanderbilt University
GPT Vision: Seeing the World through Generative AI from Vanderbilt University
Trees, SVM and Unsupervised Learning from University of Colorado Boulder
Approximation Algorithms and Linear Programming from University of Colorado Boulder
Advanced Data Structures, RSA and Quantum Algorithms from University of Colorado Boulder
Introduction to Generative AI from University of Colorado Boulder
Network Systems Foundations from University of Colorado Boulder
Machine Learning for Semiconductor Quantum Devices from Delft University of Technology
Development and Applications of Germanium Quantum Technologies from Delft University of Technology
[New] Introduction to ChatGPT. Boost your productivity to the maximum using artificial intelligence! from Universitat Politècnica de València
Componentes Tecnológicos y Operaciones from Tecnológico de Monterrey
Generative Pre-trained Transformers (GPT) from University of Glasgow
Generative AI in Education from University of Glasgow
AI Prompt Engineering for Beginners from Davidson College
Introduction to Blockchain for Business from University of Adelaide
Harnessing AI in Marketing and Communication from University of Adelaide
AI Concepts and Strategy from Rutgers University
Basics of Machine Learning from RWTH Aachen University
Generative AI in Higher Education from King’s College London
Artificial Intelligence using Prolog Programming from IGNOU
BESE-141- ICT in Education from IGNOU
New Ways of Working in an AI World from London Business School
Machine Learning for Image Data from The University of Nottingham
Introduction to DAOs: Decentralised Autonomous Organisations from RMIT University
GameFi in the Web3 World from RMIT University
AI in Healthcare. Hype or Help? from KU Leuven University
The Mathematics of Cryptography: From Ancient Rome to a Quantum Future from University of York
Machine Learning for Smart Beta from Sungkyunkwan University
Healthcare Data Management and Information Systems from Northeastern University
Machine Learning in Healthcare: Fundamentals & Applications from Northeastern University
AI Ethics, Law, and Policy from National Tsing Hua University
Applications of AI in Real Estate Finance and Investment from National Tsing Hua University
[New] Recommender Systems in Python from National Tsing Hua University
Introduction to Blockchain from Pohang University of Science and Technology
Blockchain Theory and Applications Ⅱ from Pohang University of Science and Technology
Blockchain Theory and Applications I from Pohang University of Science and Technology
OS Security from Illinois Institute of Technology
Linux OS from Illinois Institute of Technology
Computer Networking from Illinois Institute of Technology
Introduction to Data Networks and the Internet – Bachelor’s from Illinois Institute of Technology
Introduction to Data Networks and the Internet – Master’s from Illinois Institute of Technology
Introduction to Open Source Operating Systems – Bachelor’s from Illinois Institute of Technology
Introduction to Open Source Operating Systems – Master’s from Illinois Institute of Technology
Supervised Learning and Its Applications in Marketing from O.P. Jindal Global University
Unsupervised Learning and Its Applications in Marketing from O.P. Jindal Global University
Introduction to Data Strategy, Management, and Governance from IE University
Data Monetization, Management, and Trends from IE University
Blockchain Fundamentals: Understanding the Origins, Mechanisms, and Applications of Decentralized Systems from SDA Bocconi School of Management
Blockchain Implementation and Regulation: Challenges, Opportunities and Future Implications from SDA Bocconi School of Management
Lean Six Sigma Green Belt Business Project from Technische Universität München (Technical University of Munich)
Safety By Design from RMIT University
Security Management and Governance from Royal Holloway, University of London

Programming (54)

Foundations of Software Testing and Validation from University of Leeds ★★★★★(3)
An Introduction to Programming using Python from University of Leeds ★★★★★(2)
CS50’s Introduction to Programming with R from Harvard University
Statistical Learning with Python from Stanford University
Using JavaScript and JSON in Django from University of Michigan
Building Objects in C from University of Michigan
Data Structures in C from University of Michigan
Exploring C from University of Michigan
Programming in C from University of Michigan
Python Programming Fundamentals from Duke University
Rust Fundamentals from Duke University
Data Engineering with Rust from Duke University
Rust for Large Language Model Operations (LLMOps) from Duke University
[New] Python and Rust with Linux Command Line Tools from Duke University
Data Science with NumPy, Sets, and Dictionaries from Duke University
Rust for DevOps from Duke University
Introduction to Python from Arizona State University
Object-Oriented Programming and GUI with Python from Arizona State University
Data Analysis and Visualization with Python from Arizona State University
Digital Design with Verilog from Indian Institute of Technology Guwahati
JavaScript Basics from University of California, Davis
Interactivity with JavaScript and jQuery from University of California, Davis
Data Manipulation in JavaScript from University of California, Davis
Working with Integrated Development Environments from University of Leeds
Working with Version Control from University of Leeds
How to Get Into Web Development from University of Leeds
How to Get Into Software Development from University of Leeds
How to Get Into Cloud Computing from University of Leeds
Programming for a Networked World from Vanderbilt University
Building HTTP APIs with Spring from Vanderbilt University
Microservice Architectures from Vanderbilt University
Functional Programming with Java and Threads from Vanderbilt University
Platform Thinking for the Metaverse from Politecnico di Milano
Computational Thinking with JavaScript 4: Create & Deploy from University of Glasgow
Web Technology from Uttarakhand Open University, Haldwani
Data Structure using C Programming from IGNOU
Image Processing Using Python from IGNOU
Introduction to Virtual Reality from IGNOU
[New] GO Programming for Everyone: Part 1 from University of California, Santa Cruz
Introduction to Programming from Ball State University
Metaverse and Virtual Reality from National Tsing Hua University
Introduction to Java from Universidad de Palermo
[New] Object-Oriented Programming with Java from Universidad de Palermo
Relational Database Design from Illinois Institute of Technology
Introduction to Relational Databases from Illinois Institute of Technology
Mobile Computing and Cloud from Illinois Institute of Technology
Introduction to Open Source Application Development from Illinois Institute of Technology
Open Source Programming – Master’s from Illinois Institute of Technology
Programming and Application Foundations from Illinois Institute of Technology
Open Source Programming – Bachelor’s from Illinois Institute of Technology
Relational Database Implementation and Applications from Illinois Institute of Technology
[New] Fundamentals of Web Development from Illinois Institute of Technology
Python Fundamentals for Business Analytics from Lehigh University
Fundamentals of Python from SDA Bocconi School of Management

Science (99)

Biotech — From Science to Business from Technische Universität München (Technical University of Munich) ★★★★☆(3)
Agroforestry I: Principles and Practices from University of Florida
Introduction to Sharks from Taipei Medical University
RNA Biology with Eterna from Stanford University
Genetics: Population Genetics and Human Traits from Massachusetts Institute of Technology
Thermal-Fluids Engineering 1: Basics of Thermodynamics and Hydrostatics from Massachusetts Institute of Technology
Chemical Thermodynamics II: Equilibrium and Kinetics from Massachusetts Institute of Technology
Psychedelics and the Mind from University of California, Berkeley
Classics in Neuroscience from Indian Institute of Technology Madras
Fundamentals of Attosecond Science and Technology (FAST) from Indian Institute of Technology Madras
Basics of Crop Breeding and Plant Biotechnology from Indian Institute of Technology, Kharagpur
Comprehensive Molecular Diagnostics and Advanced Gene Expression Analysis from Indian Institute of Technology, Kharagpur
Elementary Thermodynamics for All from Indian Institute of Technology, Kharagpur
Principles of Extractive Metallurgy from Indian Institute of Technology, Kharagpur
Watershed Hydrology from Indian Institute of Technology, Kharagpur
Coherence and Quantum Entanglement from Indian Institute of Technology Kanpur
Introduction to Refrigeration and Air Conditioning from Indian Institute of Technology Kanpur
Laboratory Practices in Earth Sciences: Landscape Mapping from Indian Institute of Technology Kanpur
Supramolecular Chemistry-I from Indian Institute of Technology Kanpur
Tapestry of Field theory: Classical & Quantum, Equilibrium & Nonequilibrium Perspectives from Indian Institute of Technology Kanpur
निर्माण प्रबंधन (Construction Management) के सिद्धांत[Nirman prabandhan (Construction Management) ke Siddhant] from Indian Institute of Technology Kanpur
Risks to Crop Production in Agriculture from University of Illinois at Urbana-Champaign
Strategies and Tools to Mitigate Agricultural Risk from University of Illinois at Urbana-Champaign
Interpretative molecular spectroscopy from NPTEL
Many body methods in quantum chemistry from NPTEL
Quantum Mechanics I from NPTEL
Cognitive Ergonomics from Indian Institute of Technology Roorkee
Plasma Physics and Applications from Indian Institute of Technology Roorkee
Climate Solutions: Malawi from Edinburgh Climate Change Institute
Climate Solutions from University of Edinburgh
The Discovery of the Higgs Boson from University of Edinburgh
Climate Change: Carbon Capture and Storage from University of Edinburgh
Climate Solutions: UAE from University of Edinburgh
The Role of Social Sciences in Nitrogen Research from University of Edinburgh
Nitrogen Pollution – Threats to Tropical Coral Coasts from University of Edinburgh
Applied Seismology for Engineers from Indian Institute of Technology Guwahati
Applied Statistical Thermodynamics from Indian Institute of Technology Guwahati
Mechanics of Sheet Metal Forming from Indian Institute of Technology Guwahati
Quantum Entanglement: Fundamentals, measures and applications from Indian Institute of Technology Guwahati
Topology and Condensed Matter Physics from Indian Institute of Technology Guwahati
Science Communication: Research Productivity and Data Analytics using Open Source Software from Indian Institute of Technology Delhi
Sensory Science: Conducting Tests from University of California, Davis
Light and Materials from Rice University
Geometrical and Physical Optics from Rice University
Oscillators and Waves from Rice University
One and Two dimensional NMR Spectroscopy: Concepts and Spectral Analysis from Indian Institute of Science Bangalore
Human Physiology from Indian Institute of Science Education and Research, Pune
Computational Genomics from Indian Institute of Science Education and Research Bhopal
Industrial Hydraulics and Automation from IIT (ISM) Dhanbad
Mine Automation and Data Analytics from IIT (ISM) Dhanbad
Forensic Linguistics from NPTEL
Slope Engineering from The Hong Kong University of Science and Technology
Polar Peril from University of Colorado Boulder
Intro to the Arctic from University of Colorado Boulder
The North Awakens from University of Colorado Boulder
The Neuroscience of Leading Transformational Organizations from University of Colorado Boulder
The Neuroscience of Leading High-Performance Teams from University of Colorado Boulder
Spacecraft Relative Motion Kinematics and Kinetics from University of Colorado Boulder
Modern Topics in Condensed Matter Physics from University of Colorado Boulder
Universal Theories from University of Colorado Boulder
Phases of Matter: Solid, Liquid, Gas and Beyond from University of Colorado Boulder
Movements Are Controlled By Muscle Forces from University of Colorado Boulder
Fundamental Neural Pathways For Movement from University of Colorado Boulder
Movement Capabilities Depend on Neuromuscular Properties from University of Colorado Boulder
[New] Engineering Genetic Circuits: Modeling and Analysis from University of Colorado Boulder
Sustainable Building with Timber from Delft University of Technology
Industrial Fermentation from Delft University of Technology
[New] Synchrotrons and X-Ray Free Electron Lasers (part 2) from École Polytechnique Fédérale de Lausanne
Concepts and Applications in Science from Indian Institute of Management Bangalore
Physics Fundamentals: Oscillations and Waves from Universitat Politècnica de València
Physics Fundamentals: Mechanics from Universitat Politècnica de València
Physics Fundamentals: Electromagnetics from Universitat Politècnica de València
The Plastic Life Cycle: from Pollution to Solution from Wageningen University
Agroforestry II: Major Systems of the World from University of Florida
Agroforestry V: Ecosystem Services, Food and Sustainability from University of Florida
Agroforestry IV: Climate, Carbon Storage and Agroforestry from University of Florida
Agroforestry III: Principles of Plant and Soil Management from University of Florida
[New] Foundations of Life Cycle Assessment Practice from Deakin University
Is this Physics or Magic? Learning Physics through Minds-on Science Demonstration from National University of Singapore
Free Will and Neuroscience from Dartmouth College
Genetic Engineering and Its Recent Advancements from IGNOU
Industrial Safety And Fire Safety Management from IGNOU
Computational Protein Modeling and Analysis from IGNOU
Fundamentals of Computational Biology from IGNOU
Safety In Construction Industry from IGNOU
Elements of Underground and Opencast Mining from Chhattisgarh Swami Vivekanand Technical University
Signaling actions of small molecules from Korea Advanced Institute of Science and Technology
A starter’s guide to Open Science from Erasmus University Rotterdam
Cities, Climate and Change: Pathways and Opportunities from Lund University
Molecular Biology: How to Detect Pathogens in Aquaculture from Taipei Medical University
Introduction to Lasers from Taipei Medical University
Immunology (Basics) from Manipur University
Nutritional & Clinical Biochemistry from Manipur University
Photo Geology and Remote Sensing from Doctor Harisingh Gour Vishwavidyalaya, Sagar
Introduction to Biosafety for Modern Biotechnology from University of Malaya
Environmental Issues In India from Govt. Degree College, Eidgah, Srinagar
CHEMISTRY OF NANOMATERIALS from CEC
Embryology of Angiosperms from CEC
Coordination Chemistry states of matters & chemical kinetics from The Maharaja Sayajirao University of Baroda

Engineering (88)

Fundamental Skills in Engineering Design from University of Leeds ★★★★★(2)
[New] Rocket Science in Everyday Life from University of Michigan
[New] The History of Rocket Science from University of Michigan
[New] The Basics of Rocket Science from University of Michigan
Advanced Topics in Science and Technology of Concrete from Indian Institute of Technology Madras
Analog Electronic Circuits – IITM from Indian Institute of Technology Madras
Design of Mechanical Transmission Systems from Indian Institute of Technology Madras
Surface Facilities for Oil and Gas Handling from Indian Institute of Technology Madras
Aerospace Structural Analysis from Indian Institute of Technology, Kharagpur
Combustion of Solid Fuels and Propellants from Indian Institute of Technology, Kharagpur
Cryogenic Hydrogen Technology from Indian Institute of Technology, Kharagpur
EMI /EMC and Signal Integrity: Principles, Techniques and Applications from Indian Institute of Technology, Kharagpur
Embedded Sensing, Actuation and Interfacing Systems from Indian Institute of Technology, Kharagpur
Experimental Robotics from Indian Institute of Technology, Kharagpur
Fundamentals of Supersonic and Hypersonic Flow from Indian Institute of Technology, Kharagpur
Momentum Transfer in Fluids from Indian Institute of Technology, Kharagpur
Water Quality Management Practices from Indian Institute of Technology, Kharagpur
Drones for Environmental Science from Duke University
Engineering Thermodynamics in Hindi from Indian Institute of Technology Kanpur
Introduction to Aircraft Control System from Indian Institute of Technology Kanpur
Digital Communication using GNU Radio from NPTEL
Modeling Stochastic phenomena for Engineering applications: Part-1 from NPTEL
Nonlinear Control Design from NPTEL
Energy Resources, Economics, and Sustainability from Indian Institute of Technology Roorkee
RF Transceiver of Design from Indian Institute of Technology Roorkee
VLSI Physical Design with Timing Analysis from Indian Institute of Technology Roorkee
Primary and Secondary Batteries from Arizona State University
Batteries and Electric Vehicles from Arizona State University
Semiconductor Packaging Manufacturing from Arizona State University
Battery Comparison, Manufacturing, and Packaging from Arizona State University
Lithium Based Batteries from Arizona State University
Zn and Ni Based Batteries from Arizona State University
Advanced Semiconductor Packaging from Arizona State University
Introduction to Semiconductor Packaging from Arizona State University
Fundamentals of Semiconductor Characterization from Arizona State University
Electrical Characterization: Diodes from Arizona State University
Optical and X-Ray Characterization from Arizona State University
Electron and Ion Beam Characterization from Arizona State University
Electrical Characterization: MOSFETs from Arizona State University
Integrated Circuits and Applications from Indian Institute of Technology Guwahati
Introduction to Solidification Processing from Indian Institute of Technology Guwahati
Power Plant System Engineering from Indian Institute of Technology Guwahati
Structural Vibration from Indian Institute of Technology Guwahati
Computational process design from Indian Institute of Technology Delhi
Computer-Aided Design of Electrical Machines from Indian Institute of Technology Delhi
Data-Enabled Tribological Engineering: From Experiments to Predictive Models from Indian Institute of Technology Delhi
EV – Vehicle Dynamics and Electric Motor Drives from Indian Institute of Technology Delhi
GIS Applications Across Industries from University of California, Davis
Geospatial Analysis with ArcGIS from University of California, Davis
How to Get Into Robotics from University of Leeds
Basics of Semiconductor Microwave Devices from Indian Institute of Science Bangalore
Control System Design from Indian Institute of Science Bangalore
State space Approach to Control System Analysis and Design from Indian Institute of Technology Mandi
Robotic Path Planning and Task Execution from University of Colorado Boulder
Robotic Mapping and Trajectory Generation from University of Colorado Boulder
Basic Robotic Behaviors and Odometry from University of Colorado Boulder
Spacecraft Formation Flying and Control Capstone Project from University of Colorado Boulder
Spacecraft Relative Motion Control from University of Colorado Boulder
Modeling of Feedback Systems from University of Colorado Boulder
Engineering Genetic Circuits: Design from University of Colorado Boulder
[New] Exam: Photovoltaic (PV) Energy Conversion from Delft University of Technology
[New] The Thymio robot as a tool for discovering digital science from École Polytechnique Fédérale de Lausanne
Modelling and simulation of mechanical systems from University of Naples Federico II
Autonomous Aerospace Systems from University of Naples Federico II
Advanced Product Quality Planning(APQP) from Indian Institute of Management Bangalore
Concepts and Applications in Engineering from Indian Institute of Management Bangalore
Production Part Approval Process (PPAP) from Indian Institute of Management Bangalore
Out of core nuclear fuel management: front end from Universidad Nacional Autónoma de México
In core nuclear fuel management from Universidad Nacional Autónoma de México
Out of core nuclear fuel management: back end from Universidad Nacional Autónoma de México
Revit for Structural Engineers from University System of Maryland
Management of Marginal Lands and Carbon Sequestration estimation through Remote Sensing and GIS from Universitat Politècnica de València
Conservation & Project Management of Baoli Water Systems from Indian Institute of Technology Delhi
Introduction to Robotic Programming from RWTH Aachen University
4th Industrial Revolution & New Business Model from Seoul National University
Basic Principles of Energy Management & Energy Audit from IGNOU
Digital electronic and System design from IGNOU
Emerging Technologies in Renewable Energy Sources from IGNOU
Fundamental of Electronic Engineering from IGNOU
Power Generation Technologies from IGNOU
Domestic Equipment Maintenance from IGNOU
Introduction to Semiconductor Process 1 from Korea Advanced Institute of Science and Technology
Introduction to Semiconductor Process 2 from Korea Advanced Institute of Science and Technology
Core Topics in Chemical Engineering: Diffusion and Mass Transfer from Taipei Medical University
[New] System Dynamics from Fundação Instituto de Administração
Introduction to Nanoscience and Nanotechnology from Central University of Kerala
[New] Building Information Modelling (BIM) for Historic Buildings and Built Environment from University of Malaya
Unmanned Aerial Systems (UAS): Fundamentals from University of Alaska Fairbanks

Business (150)

Humanitarian Logistics from Massachusetts Institute of Technology ★★★★★(1)
Comprehensive Final Exam in Finance from Massachusetts Institute of Technology
Driving Operational Performance from University of Pennsylvania
Personal Branding: Stand Out and Succeed from University of Michigan
Creating Change through Social Entrepreneurship from Yale University
Business Intelligence & Analytics from Indian Institute of Technology Madras
Foundations of Accounting & Finance from Indian Institute of Technology Madras
Strategic Sourcing from Indian Institute of Technology Madras
Strategic Management for Churches from Duke University
Advanced Financial Instruments for Sustainable Business and Decentralized Markets from Indian Institute of Technology Kanpur
Global Impact: Cross-Cultural Management from University of Illinois at Urbana-Champaign
Global Impact: Multiculturalism from University of Illinois at Urbana-Champaign
Issues in Supply Chain Management from University of Illinois at Urbana-Champaign
Supply Chain of Agriculture from University of Illinois at Urbana-Champaign
Golf Course Management: Best Practices from University of Illinois at Urbana-Champaign
Governmental Accounting and Reporting I from University of Illinois at Urbana-Champaign
Governmental Accounting II and Nonprofit Accounting from University of Illinois at Urbana-Champaign
Business Forecasting from NPTEL
Business Fundamentals for Entrepreneurs (Part 2: External Operation) from NPTEL
Strategic Services Marketing from Indian Institute of Technology Roorkee
Mapping Digital Transformation in Supply Chain from University of Maryland, College Park
Digital Business Strategy from University of Virginia
What is Technology Entrepreneurship and Innovation? from Arizona State University
Putting it All Together: Problem-Solve Like an Entrepreneur from Arizona State University
Curiosity: A Necessary Ingredient for Successful Innovation from Arizona State University
Care: The First Step in Tech Innovation for Entrepreneurs from Arizona State University
Organizational Behaviour: Individual Dynamics in Organization from Indian Institute of Technology Guwahati
Innovation Management: Winning in the Age of Disruption from University of Leeds
Supply Chain Digitization from NPTEL
Market Research and Analysis for Tech Industries from University of Colorado Boulder
Digital Media and Strategic Planning in Technology Markets from University of Colorado Boulder
Strategic Product Development from University of Colorado Boulder
Managing the New Product Development Process from University of Colorado Boulder
Building and Pitching Marketing Campaigns in Tech Industries from University of Colorado Boulder
Introduction to Digital Advertising from University of Colorado Boulder
Programmatic Advertising from University of Colorado Boulder
Search and Display Advertising from University of Colorado Boulder
How to Implement and Evaluate Communication Campaigns from University of Colorado Boulder
Understanding the Campaign Components from University of Colorado Boulder
Product Innovation Management from University of Colorado Boulder
Integrated and Strategic Communication Campaigns from University of Colorado Boulder
A quick tour on Big Data and Business Intelligence from University of Naples Federico II
Family Business from Indian Institute of Management Bangalore
Marketing Management from Indian Institute of Management Bangalore
Operation Management from Indian Institute of Management Bangalore
People Management for Entrepreneurs from Indian Institute of Management Bangalore
Platform Business Models from Indian Institute of Management Bangalore
Organizational Design from Indian Institute of Management Bangalore
Advanced Topics in Organizational Behaviour from Indian Institute of Management Bangalore
B2B Marketing from Indian Institute of Management Bangalore ★★★★★(1)
Banking and Insurance from IIS (Deemed to be University), Jaipur
Design Thinking from Sri Balaji University
Equity Stock Market: Concepts, Instruments, Risks and Derivatives from Indian Institute of Management Bangalore
HR Analytics Using Excel from Indian Institute of Management Bangalore
Understanding Organizational Behaviour from Indian Institute of Management Bangalore
Behavioural Finance from Indian Institute of Management Bangalore
Evolution of Business and Market from Indian Institute of Management Bangalore
Foundations of Digital Business from Indian Institute of Management Bangalore
Money Banking & Financial Markets from Indian Institute of Management Bangalore
Prescriptive Analytics from Indian Institute of Management Bangalore
Gamification as a Business Strategy from Indian Institute of Management Bangalore
[New] New Age Business Models from Indian Institute of Management Bangalore
[New] Supply Chain Management from Indian Institute of Technology Roorkee
[New] Supply Chain Analytics from Indian Institute of Technology Roorkee
Remote teams leadership from Universitat Politècnica de València
Sustainable high-end tourism from Universitat Autònoma de Barcelona (Autonomous University of Barcelona)
Data-Driven Leadership Skills Course 3: Data-Driven Leaders from University of Glasgow
Data-Driven Leadership Skills Course 1: Leadership Narrative from University of Glasgow
Data-Driven Leadership Skills Course 2: Agile Leadership from University of Glasgow
Data-Driven Leadership Skills Capstone Project from University of Glasgow
MBA Essentials from University of Glasgow
[New] Data intelligence for businesses and managers from Institut Mines-Télécom
Digital Currency from The University of Hong Kong
E-Payment from The University of Hong Kong
Build an Agile Team from University of Adelaide
Create Energised and Empowered Teams from University of Adelaide
Create Innovative Teams with Design Thinking from University of Adelaide
Manage Team Performance from University of Adelaide
Manage Virtual and Hybrid Teams from University of Adelaide
Mastering Excel Pivot Tables from University of Adelaide
Customer Care Strategies for a New Business from University of Adelaide
Growth Strategies for a New Business from University of Adelaide
Innovation and Entrepreneurship for a New Business from University of Adelaide
Developing Ideas and Content for your Digital Strategy from University of Adelaide
Designing and Implementing a Leadership Development Strategy from University of Adelaide
Sourcing Excellence from Rutgers University
Supply Chain Excellence Capstone from Rutgers University
Logistics Excellence from Rutgers University
Operations Excellence from Rutgers University
Market Strategy Essentials: Solving Business Problems Through Trend and Competitor Analysis from University of Cape Town
Leveraging Customer Insights and Data from University of Cape Town
Data-Driven Marketing: Interpretation, Storytelling and the Future of Market Research from University of Cape Town
Commercial Property and Opportunity from University of Cape Town
Commercial Property Contracts and Financial Modelling from University of Cape Town
Commercial Property Valuation from University of Cape Town
Alternative Property Investment Opportunities from University of Cape Town
Introduction to Values-Based Leadership from University of Cape Town
Adopting a Values-Based Approach in an Organization from University of Cape Town
Becoming a Values-Based Leader from University of Cape Town
Art and the Digital Transformation from Copenhagen Business School
Introduction to Digital Transformation: Change & Disruption from London Business School
Business for Good: Fundamentals of Corporate Responsibility from London Business School
Agile Organisation: Strategies for Business Resilience from London Business School
Entrepreneurial Competencies for Landscape Restoration from Erasmus University Rotterdam
Pubs: History, Consumers, Management, and Protection from University of York
Business Research Methods from Taipei Medical University
[New] Fundamentals of Management and Organizations from Fundação Instituto de Administração
[New] Leading Transformation from Fundação Instituto de Administração
[New] Operations Management from Fundação Instituto de Administração
[New] Global Supply Chain Management from Fundação Instituto de Administração
[New] Strategic Management from Fundação Instituto de Administração
[New] Scenario Planning I from Fundação Instituto de Administração
[New] Scenario Planning II from Fundação Instituto de Administração
[New] Entrepreneurship from Fundação Instituto de Administração
[New] Introduction to Strategy from Fundação Instituto de Administração
[New] Corporate Foresight from Fundação Instituto de Administração
[New] Valuation & Strategic Finance from Fundação Instituto de Administração
[New] Financial Accounting from Fundação Instituto de Administração ★★★★★(1)
[New] Strategic Marketing from Fundação Instituto de Administração
[New] Fundamentals of Marketing from Fundação Instituto de Administração
Corporate Finance: A Beginner’s Guide from University of Padova
[New] Modélisation des processus d’affaires avec BPMN from HEC Montréal
Business Communication from Jai Narain Vyas University, Jodhpur ★★★★★(1)
CORPORATE ACCOUNTING from Jai Narain Vyas University, Jodhpur
Fundamentals of Digital Transformation and Data Analytics from National Tsing Hua University
Human Resource Analytics from National Tsing Hua University
Entrepreneurship for Sustainability and Wellbeing in an Era of Digitalisation from Hanken School of Economics
Advanced Digital Transformation (Part 2) from Indian Institute of Management Ahmedabad
Advanced Digital Transformation (Part 1) from Indian Institute of Management Ahmedabad
Advanced Digital Transformation (Part 3) from Indian Institute of Management Ahmedabad
Building Strategic Foresight Capabilities from EDHEC Business School
Competitive Strategy from Illinois Institute of Technology
Mastering Excel Essentials to Enhance Business Value from Illinois Institute of Technology
Business Economics and Game Theory for Decision Making from Illinois Institute of Technology
Innovation and International Strategy from Illinois Institute of Technology
A Comprehensive Excel Masterclass from Illinois Institute of Technology
Financial Statement Applications from Illinois Institute of Technology
[New] Leadership & Organization Design from Illinois Institute of Technology
Digital Marketing Analytics from O.P. Jindal Global University
Principles of Management from O.P. Jindal Global University
Introduction to Decision Science for Marketing from O.P. Jindal Global University
Leadership: How to Build High Performing Teams and Culture from University of Lincoln
Human Resources: Acquiring and Managing Talent in the 21st Century from University of California, Riverside
Foundations of Predictive Analytics: Regression and Classification from IE University
Predictive Analytics for Business Planning: Time-Series Forecasting from IE University
Digital Supply Chain Management from SDA Bocconi School of Management
Leadership essentials – leading self to lead others from SDA Bocconi School of Management
Digital Marketing: New Trends and Technologies from Nottingham Trent University
Leadership tools for ethical problem-solving from Nottingham Trent University
Foundations of Marketing Essentials from Manipal University Jaipur

Personal Development (38)

Thriving 101: Designing a Fulfilling Life & Career from University of Colorado Boulder
[New] Internal Communications Framework from University of California, Irvine
[New] External Communications Channels from University of California, Irvine
[New] Introduction to Corporate Communications from University of California, Irvine
Finding Purpose Across Your Life from University of California, Berkeley
Introduction to Research (New: Research Methodology) from Indian Institute of Technology Madras
Multi-Criteria Decision Making and Applications from Indian Institute of Technology Kanpur
Online Communication in the Digital Age from Indian Institute of Technology Roorkee
[New] Emotional Intelligence from Arizona State University
Introduction to Negotiation Strategy from University of California, Davis
Navigating Negotiation Intricacies from University of California, Davis
Δεξιότητες ομαδικής εργασίας: Αποτελεσματική επικοινωνία from University of Colorado Boulder
How Self-Motivation Shapes Personal Success from University of Colorado System
Overcoming Challenges in Self and Society from University of Colorado System
Business Negotiations from Indian Institute of Management Bangalore
Teamwork in face-to-face, remote and hybrid environments from Universitat Politècnica de València
[New] Interpersonal Communication Skills adapted to remote teams from Universitat Politècnica de València
How to Give and Receive Feedback from Davidson College
Wellness and Stress Management from Davidson College
Become a changemaker, build a career with purpose and impact from HEC Paris
Persuasive Communication from IESE Business School
The Role of the Media from IESE Business School
OUL-002 Tarseel Aur Fahem-O-Idraak from IGNOU
MJM024: Media Information and Empowerment (Tamil) from IGNOU
MJM024: Media Information and Empowerment (Hindi) from IGNOU
Digital Media Literacy from IGNOU
Introduction to 21st Century Skills from University of Wisconsin–Madison
Teaching Teamwork & Communication Skills from University of Wisconsin–Madison
Teaching Critical Thinking & Self-Regulated Learning Skills from University of Wisconsin–Madison
[New] Communication Principles for Leaders from Fundação Instituto de Administração
[New] Career Management from Fundação Instituto de Administração
[New] Delphi Method from Fundação Instituto de Administração
[New] Decision Making from Fundação Instituto de Administração
[New] Information Literacy: Skills for Researchers from University of Malaya
Intercultural Communications in the Workplace from London School of Economics and Political Science
Computer and Peripheral Hardware from Illinois Institute of Technology
Microsoft Windows OS from Illinois Institute of Technology
Digital Literacy: Sustainable Development in the Information Age from Chung Yuan Christian University

Humanities (87)

BSKLA-135: Sanskrit Bhasha aur Sahitya from IGNOU
Chinese Language in Culture: Level 3 from Massachusetts Institute of Technology
[New] Exploring Algorithmic Bias as a Policy Issue: A Teach-Out from Johns Hopkins University
Становлення сучасної України from Yale University
Introduction to Exercise Physiology & Sports Performance from NPTEL
Modern Food Packaging Technologies: Regulatory Aspects and Global Trends from Indian Institute of Technology, Kharagpur
Japani Bhasha – Saral swaroop from Indian Institute of Technology Kanpur
Sports Turf Management: Best Practices from University of Illinois at Urbana-Champaign
Indigenous Languages: From Policy and Planning to Implementation and Assessment from The University of British Columbia
Beer Quality Systems from University of California, Davis
Spanish Vocabulary: Meeting People from University of California, Davis
Spanish Vocabulary: Sports, Travel, and the Home from University of California, Davis
Spanish Vocabulary: Cultural Experience from University of California, Davis
Spanish Vocabulary: Careers and Social Events from University of California, Davis
Vulnerability Studies: An Introduction from University of Hyderabad
Philosophy and Critical Thinking from NPTEL
Computing, Ethics, and Society Foundations from University of Colorado Boulder
A Theoretical Origin of Ethics in Business and Tech Industry from University of Colorado Boulder
Avoiding Ethical Pitfalls in the Tech Industry from University of Colorado Boulder
Ethical Issues in Computing Applications from University of Colorado Boulder
Ethical Issues in AI and Professional Ethics from University of Colorado Boulder
Wilderness First Aid – Environmental Emergencies from University of Colorado System
Exploring the Origins of Selfhood from University of Colorado System
English Lower Intermediate B1.1 from University of Naples Federico II
Understanding Domestic Violence from Curtin University
Writing for Business Advanced from University of Glasgow
Reading and Comprehension of Text in English from Universidad Autónoma de Madrid
Crisis Communications from IESE Business School
[New] Academic Writing from University of Adelaide
Introduction to Feature Journalism from University of Cape Town
Developing Feature Stories from University of Cape Town
Writing Feature Articles from University of Cape Town
AP® Italian Language and Culture (2023-2024) from Wellesley College
English Communication from CEC
The Basics of Libertarian Free Will from Dartmouth College
Neural Basis of Imagination, Free Will, and Morality from Dartmouth College
Reading and Reflecting on Text from IGNOU
BSKC-102: Sanskrit Sahitya ka Allochanatmak Vishleshan from IGNOU
OUL – 003 History of Urdu Language & Literature from IGNOU
OUL-001 Huroof Shanasi Aur Talaffuz from IGNOU
OULE – 001 Contemporary Urdu Poetry from IGNOU
OULE – 002 Contemporary Urdu Fiction from IGNOU
OULE – 005 Principle of Translation from IGNOU
SSB-001: Pratham Bodhah from IGNOU
SSB-002: Dwitiya Bodhah from IGNOU
SSB-003: Sambhashanam from IGNOU
Assamese Poetry: From Ancient to Modern Period from IGNOU
Introduction to Functional English from IGNOU
Essentials of Indian Philosophy from IGNOU
MEG-07: Indian English Literature from IGNOU
BLI-221: Library Infromation and Society from IGNOU
MEG-03: British Novel from IGNOU
MEG-05: Literary Theory & Criticism from IGNOU
MEG-10: English Studies in India from IGNOU
MEG-06: American Literature from IGNOU
MEG-13: Writings from the Margins from IGNOU
[New] English in the Workplace: Soft skills from Pontificia Universidad Católica de Chile
European History, Society and Culture from KU Leuven University
Business History of the FIFA World Cup from University of York
日本の近代化: 福澤諭吉の格闘 from Keio University
Abhidhamma (Pali) from UGC
The Rise of K-Culture: Discover the Korean Wave (Hallyu) from Hanyang University
History of India-II from University of Kashmir
[New] Cultural Dialogues: An Intercultural Reading of The Analects and Tao Te Ching from Shanghai International Studies University
[New] A Panoramic View of China: Introducing Chinese Culture from Shanghai International Studies University
Unlocking the Secrets of the Chinese Language from University of Malaya
Buddhist Philosophy from UGC
Buddhist Tourism from UGC
History of Indian Buddhism from UGC
ECONOMIC HISTORY OF INDIA FROM 1857 TO 1947 from CEC
Indian Culture & History from Shri Lal Bahadur Shastri National Sanskrit University
History of India-I( Ancient India ) from CEC
हिन्दी भाषा एवं संप्रेषण / Hindi Bhasha Evam Sampreshan from CEC
Introduction to Teaching Creative Writing from Manchester Metropolitan University
Iñupiaq Language and Culture from University of Alaska Fairbanks
Central Yup’ik Language and Culture from University of Alaska Fairbanks
Ethics in Public Policy from O.P. Jindal Global University
Learn Mandarin: How to Express Health Issues in Chinese from National Yang Ming Chiao Tung University (NCYU)
Learn Mandarin: Food and Drink in Taiwan from National Yang Ming Chiao Tung University (NCYU)
Learn Mandarin: Shopping and Daily Life In Taiwan from National Yang Ming Chiao Tung University (NCYU)
Mandarin Chinese in Motion: Your Very First Chinese Class from National Yang Ming Chiao Tung University (NCYU)
Mandarin Chinese in Motion: Essay-Writing Skills from National Yang Ming Chiao Tung University (NCYU)
Introduction to Writing Fiction from University of Lincoln
How to Get Your Feature Articles Published from University of Lincoln
Mandarin Chinese in Motion: Chinese Culture on TV from National Yang Ming Chiao Tung University (NCYU)
English Composition from Thomas Edison State University
Social Formations and Cultural Patterns of the Medieval World from Dhanamanjuri University

Cybercrime from Royal Holloway, University of London ★★★★★(1)
Diversity, Equity and Inclusion: Disparities in Healthcare from Stanford University
Strategies To Improve and Incorporate Diversity, Equity and Inclusion in Healthcare from Stanford University
Introduction to Nonprofit Law from University of Pennsylvania
Medieval Hebrew Manuscripts and their Scribes from University of Pennsylvania
Using Public Policy for Social Change from University of Michigan
Affirmative Action in Higher Education Teach-Out from University of Michigan
[New] Ongoing U.S. Settler Colonialism & Native Peoples Teach-Out from Johns Hopkins University
[New] Fundamentals of Economics from University of California, Berkeley
[New] Advanced Concepts in Economics from University of California, Berkeley
[New] Real-World Applications of Economics from University of California, Berkeley
[New] Become a Peer Sponsor: Intro to Military Transition Support from Columbia University
An Introduction to Urban Ecological Heritage: Theories and Applications from Indian Institute of Technology, Kharagpur
Centre-State Relations in India from Indian Institute of Technology, Kharagpur
International Trade Law from Indian Institute of Technology, Kharagpur
Medical Law from Indian Institute of Technology, Kharagpur
Sociology and Sanitation: An Introduction from Indian Institute of Technology Kanpur
Moving the Needle at Work: Diversity, Equity and Inclusion from University of Illinois at Urbana-Champaign
Learning for a Sustainable Future from University of Edinburgh
Learning for a Sustainable Future: Live at COP28 from University of Edinburgh
Psychology of Emotion: Theory and Applications from Indian Institute of Technology Guwahati
Introduction to Intellectual Property from Indian Institute of Technology, Kharagpur
Social Model of Disability from University of Leeds
Principles of Economics: Macroeconomics – The Big Picture from Rice University
Principles of Economics: Introduction – Getting to Know You from Rice University
Principles of Economics: Microeconomics – Down to Business from Rice University
Constitution Law and Public Administration in India from National Law School of India University
Water Cooperation and Diplomacy from University of Geneva
Introduction to Political Citizenship from University of Geneva
Humanitarian Action in the Digital Age from École Polytechnique Fédérale de Lausanne
Comparative Research Designs and Methods from University of Naples Federico II
Comparative Political Systems from University of Naples Federico II
Understanding Political Concepts from University of Naples Federico II
Global Politics from University of Naples Federico II
Paths to a Sustainable Future from ESSEC Business School
Foreign Exchange market from Indian Institute of Management Bangalore
Humanities and Social Sciences from Indian Institute of Management Bangalore
Igualdad de género y derechos humanos from Universidad Nacional Autónoma de México
经济学原理（微观部分） from Tsinghua University
Tecnología accesible para la inclusión from Universitat Politècnica de València
Migration Law from Université catholique de Louvain
Exploring Models of Disability from Curtin University
Introduction to Environmental Cost-Benefit Analysis from Deakin University
Trauma, Neuro, and Shame Awareness: Best Practice for Professionals, Organisations, and Communities from Deakin University
Introduction to Diversity and Inclusion: The Employee, Business, Societal, and Personal Case from University of Cape Town
Navigating Workplace Equality: Understanding Discrimination, Privilege, and Power Dynamics from University of Cape Town
Building Inclusive Workplaces: Adapting to Change, Embracing Diversity, and Fostering Inclusive Leadership from University of Cape Town
Mechanics & Origins of Bipedalism from Dartmouth College
Experiments and Variations in Bipedalism from Dartmouth College
Inquiries Into Bipedalism from Dartmouth College
Gender Equality from University of Western Australia
Worldviews – From Sustainability to Regeneration from ETH Zurich
BCOC-133: Business Law from IGNOU
MSD 019: Global Strategies to Sustainable Development from IGNOU
Satat Vikas ke Liye Sampreshan evam Vistar from IGNOU
Sociology of Health and Illness from IGNOU
Micro Economics for Business from IGNOU
Population and Society from Krishna Kanta Handiqui State Open University
Advancing Social Impact with Digital Technologies from RMIT University
Governance in the European Union from KU Leuven University
European Union Law from KU Leuven University
Global Challenges for a Sustainable Society from KU Leuven University
Business Law from Savitribai Phule Pune University
Introductory Macroeconomics from Savitribai Phule Pune University
Corporate Sustainability from Taipei Medical University
Shaping the Future Through Sustainable Development from Taipei Medical University
SDG 14: Global Action for Marine Conservation from Taipei Medical University
Sustainable Building and Energy Efficiency Development from Taipei Medical University
Understanding the Italian Legal System: Public Law and Public Institutions from University of Padova
Advanced Archaeological Remote Sensing: Site Prospection, Landscape Archaeology and Heritage Protection in the Middle East and North Africa from Durham University
Social Formations and Cultural Patterns of the Ancient World from CEC
HEALTHY URBAN SYSTEMS – PART 1 from University of Lausanne
Healthy Urban systems Part 2 : Theories, models and tools from University of Lausanne
Sociology of India – 1 from CEC
Understanding Political Theory from CEC
Child development (B.ED) from Principal, Thiagarajar College of Preceptors, Madurai
Introduction to Public Administration_PG from Chaudhary Devi Lal University
Mathematical Methods for Economics-I from CEC
Managerial Economics: Buyer and Seller Behavior from Illinois Institute of Technology
How to Become an International Arbitrator from College of Law
International Arbitration: Frameworks and Drafting an Arbitration Agreement from College of Law
International Arbitration: Process and Procedure from College of Law
Vision 2030 (EN) from Zurich University of Applied Sciences
[New] Providing Harm Reduction Services for Drug Users and Sex Workers from Zurich University of Applied Sciences
Designing Play-Based Learning from Federation University
Gender, Climate Justice, and Food Systems Resilience from University Of The West Indies
POLITICAL THEORY: CONCEPTS & DEBATES from Vidyasagar University
Economics Fundamentals for Business Analytics from Lehigh University
Introduction to the UN Sustainable Development Goals from Chung Yuan Christian University

International (130)

Ciencia de Datos: Fundamentos de R from Harvard University
Persone, tecnologia e futuro della mobilità from University of Michigan
Personnes, technologie et futur de la mobilité from University of Michigan
Las personas, la tecnología y el futuro de la movilidad from University of Michigan
Menschen, Technologie und die Zukunft der Mobilität from University of Michigan
人、テクノロジー、そしてモビリティの未来 from University of Michigan
사람, 기술, 모빌리티의 미래 from University of Michigan
Цифровые медиа в сфере здравоохранения from Yale University
Media Digital untuk Hasil Kesehatan from Yale University
借助数字媒体实现卫生成果 from Yale University
Meios digitais para resultados na saúde from Yale University
Становление современной Украины from Yale University
Στρατηγικές επικοινωνίας για την εικονική εποχή from University of Toronto
조직적 다양성, 형평성, 포용성의 핵심 개념 from Rice University
조직 내에서 다양성, 형평성, 포용성의 정의 from Rice University
Chinese Characters for beginner (3) 汉字(3) from Peking University
Vivre avec le TDAH à travers les âges from University of Geneva
Cognition sociale from University of Geneva
Dénommer le monde : la politique des toponymes from University of Geneva
Information, Calcul, Communication: Introduction à la pensée informatique from École Polytechnique Fédérale de Lausanne
中國園林文學 (二) (Chinese Garden Literature (2)) from National Taiwan University
IA generativa en el aula from Universidad Nacional Autónoma de México
Gobierno corporativo: estructuras from Universidad Nacional Autónoma de México
Gobierno corporativo: antecedentes from Universidad Nacional Autónoma de México
Gobierno corporativo: normatividad aplicable from Universidad Nacional Autónoma de México
Con gafas violeta: igualdad de género en la escuela from Universidad Nacional Autónoma de México
Python: de cero a usuario from Universidad Nacional Autónoma de México
El águila, el nopal y ¿la serpiente? from Universidad Nacional Autónoma de México
神经光子学 from Tsinghua University
经济学原理（宏观部分） from Tsinghua University
区块链和加密数字货币 from Tsinghua University
中国经济概论 from Tsinghua University
大学历史与文化 from Tsinghua University
实用日语会话（Practical Japanese Conversation） from Tsinghua University
出土文献的新发现 from Tsinghua University
机械制造实习 from Tsinghua University
Grasshopper参数化设计与建模 from Tsinghua University
流体力学 from Tsinghua University
Fundamentos de sistemas embebidos con Arm: Primeros pasos from Arm Education
Fundamentos de ciberseguridad para usuarios from Universitat Politècnica de València
Introducción a la sostenibilidad en los servicios de agua con Qatium from Universitat Politècnica de València
Evaluación de valores: Identificación de talento y cultura organizativa from Universitat Politècnica de València
Introducción a ChatGPT.¡Impulsa tu productividad al máximo usando inteligencia artificial! from Universitat Politècnica de València
Células y tejidos from Universitat Politècnica de València
Visualización de Datos – Gestión Empresarial from Tecnológico de Monterrey
Habilidades de pensamiento y solución de problemas from Tecnológico de Monterrey
Credenciales Alternativas: el futuro de las certificaciones from Tecnológico de Monterrey
El consumidor digital from Tecnológico de Monterrey
Habilidades de pensamiento y solución de problemas from Tecnológico de Monterrey
Transformación Digital en el Retail y su interfase con el cliente. from Tecnológico de Monterrey
Visualización de Datos – Impacto en la Gestión Empresarial from Tecnológico de Monterrey
Transformación Digital y Omnicanalidad from Tecnológico de Monterrey
Mercadotecnia y Comunicación robustecidas e unificadas from Tecnológico de Monterrey
Planeación Estratégica from Tecnológico de Monterrey
Credenciales Alternativas: el futuro de las certificaciones from Tecnológico de Monterrey
Principales procesos grupales en las organizaciones from Universitat Autònoma de Barcelona (Autonomous University of Barcelona)
Interacción social y cultura organizacional from Universitat Autònoma de Barcelona (Autonomous University of Barcelona)
Las organizaciones en el siglo XXI y su relevancia social from Universitat Autònoma de Barcelona (Autonomous University of Barcelona)
Estrategias para desarrollar el talento en organizaciones from Universitat Autònoma de Barcelona (Autonomous University of Barcelona)
Cómo captar talento en la era de la digitalización from Universitat Autònoma de Barcelona (Autonomous University of Barcelona)
Competencias clave para profesionales de Recursos Humanos from Universitat Autònoma de Barcelona (Autonomous University of Barcelona)
Feminismo, género y política from Universitat Autònoma de Barcelona (Autonomous University of Barcelona)
[New] La Economía Circular: ¿un mito o una posibilidad? from Universitat Autònoma de Barcelona (Autonomous University of Barcelona)
Edición de vídeo y postproducción con DaVinci Resolve. Prácticas from Universidad Carlos iii de Madrid
Docencia con pedagogía activa mediada con tecnología digital from Universidad de los Andes
Diseño de cursos para la comprensión de Grandes Ideas from Universidad de los Andes
Análisis del contexto para fundamentar diseño de instrucción from Universidad de los Andes
Lectura crítica: proceso, niveles y herramientas from Universidad de los Andes
Realidad Extendida y Metaverso para todos from Universidad de los Andes
Introducción al deep learning contemporáneo from Universidad de los Andes
Вступ до історії гуманітарної допомоги: Introduction to Humanitarian Aid (UKR) from Deakin University
[New] Traitement d’images : analyse fréquentielle et multi-échelle from Institut Mines-Télécom
Aprendizaje-Servicio: transformación social y desarrollo sostenible from Universidad Autónoma de Madrid
Análisis visual con Tableau from Universidad Austral
Introducción a la contabilidad: comienza tu emprendimiento. from Universidad Austral
Finanzas para emprendedores from Universidad Austral
[New] Emprender en Web3 from Universidad Austral
Αλλαγή νοοτροπίας from McMaster University
MHD-03: उपन्यास एवं कहानी from IGNOU
MGPE-006: Gandhi’s Economic Thought from IGNOU
لغة البرمجة C++ لمبرمجي C، الجزء (ب) from University of California, Santa Cruz
[New] Nachhaltigkeit lehren lernen from University of Zurich
Fundamentos de sistemas recomendadores from Pontificia Universidad Católica de Chile
English for Interactions in the Workplace Intermediate Level from Pontificia Universidad Católica de Chile
Transferencia de momentum, calor y masa computacional from Pontificia Universidad Católica de Chile
Bienvenidos al español: A1.1 from Pontificia Universidad Católica de Chile
Trabajando en la preparación para el cambio educativo from Universidad de Chile
Metodologías ágiles para procesos de innovación abierta from Universidad Nacional de Córdoba
Generación de emprendimientos de Base Tecnológica from Universidad Nacional de Córdoba
Trayecto Formativo en Innovación Abierta, Emprendedurismo y Vinculación from Universidad Nacional de Córdoba
Liderazgo con impacto from Pontificia Universidad Católica del Perú
Finanzas para todos from Pontificia Universidad Católica del Perú
Introducción a la Responsabilidad Social Universitaria from Pontificia Universidad Católica del Perú
Relación entre Branding y Marketing from Pontificia Universidad Católica del Perú
Introducción al Desarrollo de Software from Pontificia Universidad Católica del Perú
Proyecto Final de Fundamentos de UX y requisitos de software from Pontificia Universidad Católica del Perú
Fundamentos de la Ingeniería de Requisitos from Pontificia Universidad Católica del Perú
Fundamentos de UX para el desarrollo de software from Pontificia Universidad Católica del Perú
Estrategia de Identidad de una Marca from Pontificia Universidad Católica del Perú
Gestión de la Diversidad, Equidad, Inclusión y Pertenencia from Pontificia Universidad Católica del Perú
[New] Herencia negra, aplicación de ritmos afroperuanos from Pontificia Universidad Católica del Perú
Storytelling: comunica tus ideas con impacto from Universidad del Rosario
Género y sexualidad: bases conceptuales y perspectivas críticas. from Universidad del Rosario
Gestión inteligente de los destinos turísticos from Universidad del Rosario
Social listening en la estrategia de marketing from Universidad del Rosario
Del aperitivo al postre: armonización de vinos, comida y situaciones from Universidad del Rosario
Mejorar la evaluación para mejorar el aprendizaje from Universidad del Rosario
Debates contemporáneos en género y sexualidad from Universidad del Rosario
Herramientas pedagógicas para combatir el racismo en las aulas from Universidad del Rosario
Français élémentaire 1 from Université de Montréal
Storytelling – Relanza tu Marca from Universidad de Palermo
Disrupción Digital from Universidad de Palermo
Felicidad y Calidad de Vida from Universidad de Palermo
Toma de Decisiones from Universidad de Palermo
Liderazgo y Desarrollo Personal from Universidad de Palermo
Gestión del Talento from Universidad de Palermo
Felicidad y Políticas Públicas from Universidad de Palermo
Cómo ser un gran líder from Universidad de Palermo
Programación Orientada a Objetos con Java from Universidad de Palermo
Introducción a Java from Universidad de Palermo
Tu camino a la felicidad familiar from Universidad de Palermo
La Economía de la Felicidad from Universidad de Palermo
Liderazgo y comunicación from Universidad de Palermo
Trastorno por Déficit de Atención con Hiperactividad (TDAH) from Universidad de Palermo
Introducción a la Hotelería y el Turismo from Universidad de Palermo
[New] Negociación y Resolución de Conflictos from Universidad de Palermo
La noción de ética para la vida profesional from Universidad Nacional de Colombia
Identidad digital: ¿Cómo tener visibilidad académica? from Universidad Nacional de Colombia
Ciencia de datos energéticos from Universidad Nacional de Colombia
Patentes: un recorrido desde su significado hasta su búsqueda from Universidad Nacional de Colombia

Health & Medicine (91)

Partnering with Patients and the Public in Co-Production from Stanford University
Understanding Psychosis from University of Michigan
Alexander Technique: Balanced Posture for Ease and Comfort from University of Michigan
Assessing Health Program Delivery from Johns Hopkins University
Health Equity Research & Practice: Local & Global Lessons from Johns Hopkins University
Analysis and Interpretation of Large-Scale Programs from Johns Hopkins University
Global Health Program Equity and Quality: Plan and Manage from Johns Hopkins University
Gender Foundations in Health Data: A Data for Health Course from Johns Hopkins University
Building Alliances in Global Health: From Global to Local from Johns Hopkins University
Public Health Advocacy Academy from Columbia University
[New] Hacking COVID-19 — Course 5: Tracing SARS-CoV-2’s Evolution from University of California, San Diego
Sports and Performance Nutrition from Indian Institute of Technology Madras
Strength & Conditioning for the Indian Population from NPTEL
An Overview on Maternal Health Antenatal, Intranatal and Postnatal Care from Indian Institute of Technology, Kharagpur
Pharmacognosy & Metabolic Engineering from Indian Institute of Technology, Kharagpur
[New] Stress First Aid for Healthcare Workers: A Peer Support Tool from Duke University
Maternal Infant Young Child Nutrition (Hindi) from NPTEL
Health Economics from Indian Institute of Technology Roorkee
Reign of Pain from Michigan State University
[New] Transmitting and Fighting Infectious Diseases from University of Leeds
Anatomy & Physiology: Filtration and Reproduction from Rice University
Anatomy & Physiology: Fluids, Transport, and Defense from Rice University
Anatomy & Physiology: Exchange and Energy from Rice University
Nursing Research: Principles and Methods(护理研究：基本原理与方法) from Peking University
[New] Oncology Nursing（肿瘤护理） from Peking University
[New] Health Care and Promotion for Infants and Toddlers from Peking University
Microsensors, Implantable Devices and Rodent Surgeries for Biomedical Applications from NPTEL
A life with ADHD from University of Geneva
Public Health Approaches to Abortion from Emory University
Health Communication from Indian Institute of Management Bangalore
Health care Communication from Indian Institute of Management Bangalore
[New] Ageing Well: Nutrition and Exercise for Older Adults from University of Reading
XR in Healthcare Education and Clinical Practice from Imperial College London
Living with Deafness and Hearing Impairment from University of East Anglia
Interview Skills for University Nursing Programme Applicants from University of East Anglia
Nutrition for Healthy Ageing from Wageningen University
Fundamentals of Aesthetic Dentistry from The University of Hong Kong
[New] 2D and 3D Modalities for Diagnostic Imaging in Dental Medicine from The University of Hong Kong
Fundamentals of Point of Care Ultrasound from National University of Singapore
Focused Cardiac & Lung Ultrasound: The Basics from National University of Singapore
Advanced Cardiac Point of Care Ultrasound from National University of Singapore
[New] Measuring Pharmacodynamics: From Ligand Binding to Clinical Outcomes from Davidson College
[New] Introduction to Pharmacokinetics: From ADME to PK/PD from Davidson College
[New] Preclinical Safety: From In Vitro Assays to Human Dose Predictions from Davidson College
[New] Lead Discovery & Optimization for Efficacy, PK, & Safety from Davidson College
[New] Literature Case Studies in Drug Discovery from Davidson College
Introduction to Small Molecule Drug Discovery & Development from University of Cape Town
Mental Health, Mindfulness, and Self-Care from University of Cape Town
Conducting Health Research in Conflict Settings: Navigating Research Challenges for Impactful Evidence from King’s College London
Reflections from 40 Years Fighting International Epidemics from Dartmouth College
Basic Anatomy for Everyone from Seoul National University
Opioids and Surgery from University College London
How to Drive Sustainable Healthcare: Educate, Engage, and Empower from University College London
Pathways to Public Health from George Washington University
History of Maternal and Child Health from George Washington University
Maternal and Child Health Foundations from George Washington University
Women’s Health from George Washington University
Capstone: Maternal and Child Health from George Washington University
Biomedical Instrumentation & Sensors from IGNOU
Medicaid Policy & Politics from University of Arizona
Dying Well: The Role of Palliative Care and Sedation in End of Life Care from Lancaster University
Super-Aged Japan: Exploring Activity, Health, and Place from Waseda University
Global Health Security: Policies and Organisations from Taipei Medical University
Yoga Volunteers for Diabetes Management Part 1 from AICTE
Yoga Volunteers for Diabetes Management Part 2 from AICTE
Yoga Volunteers for Hypertension / Heart Disease Part 1 from AICTE
Yoga Volunteers for Hypertension / Heart Disease Part 2 from AICTE
Yoga Volunteers for Palliative Care – Part 1 from AICTE
Yoga Volunteers for Palliative Care – Part 2 from AICTE
Yoga for Anger Management from AICTE
Yoga for Ego Management from AICTE
Yoga for IQ Development from AICTE
Yoga for Stress Management from AICTE
Yoga for Eye Sight Improvement from AICTE
Yoga for Physical Stamina from AICTE
Yoga for Concentration from Swami Vivekananda Yoga Anusandhana Samsthan
Yoga for Creativity from Swami Vivekananda Yoga Anusandhana Samsthan
Yoga for Memory Development from Swami Vivekananda Yoga Anusandhana Samsthan
Yoga for Voice Culture from Swami Vivekananda Yoga Anusandhana Samsthan
Advanced Research Techniques in Parasitology from University of Malaya
Laboratory Biosafety: Introduction to Risk Assessment and Managing Biohazards from University of Malaya
Health and Fitness: How to Design a Diet and Exercise Program from University of Malaya
Caring for Caregivers: Empowering Those Who Care For Older Persons from University of Malaya
Building a Healthy Plate from Tufts University
Healthcare Financial Management Fundamentals from Northeastern University
An Overview of the U.S. Healthcare System from Northeastern University
Understanding the U.S. Healthcare Landscape from Northeastern University
Introduction to ADHD: What It Is and How It’s Treated from Universidad de Palermo
Nutrition and Healthy Living from University of California, Riverside
Foundation of HTA, economic evaluation and value-based healthcare from SDA Bocconi School of Management
Fundamentals of Naturopathic Medicine from Southern Cross University

Education & Teaching (21)

Applying to College 101 from University of Pennsylvania
Student Debt Crisis Teach-Out from University of Michigan
Series Orientation: Transforming Education from University of Michigan
[New] Envisioning Educational Transformation from University of Michigan
Blended Learning Toolkit from Columbia University
Using Educational Technology with English Learners from Rice University
The Role of Culture in Teaching English Learners from Rice University
Academic Success for English Learners from Rice University
Teaching for Justice and Inclusivity In Challenging Times from University of Colorado Boulder
Designing Learning Innovation: an introduction from Politecnico di Milano
The Learning Innovation Network from Politecnico di Milano
BES-122: Contemporary India and Education from IGNOU
Media and Information Literacy for Techers from IGNOU
School Management and Leadership from IGNOU
Introduction to Distance and Digital Education from Krishna Kanta Handiqui State Open University
Successful PhD Supervision: A Shared Journey from University of Groningen
Becoming a Language Friendly Teacher from Erasmus University Rotterdam
Pathways to Success: Making the Most of Your Time at University from University of York
Introduction to Social-Emotional Learning (SEL) from University of California, Riverside
Introduction to the Finnish Education System from University of Jyväskylä
Preparing for Higher Education from Arden University

Data Science (39)

Arranging and Visualizing Data in R from University of Michigan
Data Visualization with Python from Duke University
Spark, Hadoop, and Snowflake for Data Engineering from Duke University
Multivariate Procedures with R from Indian Institute of Technology Kanpur
Data Visualization for Genome Biology from University of Toronto
Value Creation with Dark Data from Arizona State University
Extracting Value from Dark Data: ULEADD from Arizona State University
Dark Data Basics – Understanding the Unknown from Arizona State University
Programming for Data Science from University of Leeds
Exploratory Data Analysis from University of Leeds
Fundamental Tools of Data Wrangling from University of Colorado Boulder
Data Analysis with Python Project from University of Colorado Boulder
Association Rules Analysis from University of Colorado Boulder
Clustering Analysis from University of Colorado Boulder
Data Wrangling with Python Project from University of Colorado Boulder
Classification Analysis from University of Colorado Boulder
Data Processing and Manipulation from University of Colorado Boulder
Data Understanding and Visualization from University of Colorado Boulder
Data Collection and Integration from University of Colorado Boulder
Data Driven Decision Making from University of Colorado Boulder
Data Acquisition, Risk, and Estimation from University of Colorado Boulder
[New] Statistics and Data Analysis with Excel, Part 1 from University of Colorado Boulder
Foundation of Data Science from Indian Institute of Management Bangalore
Quantitative and Mixed Methods Research for Management from Indian Institute of Management Bangalore
Data Visualization and Storytelling from Davidson College
Critical Evaluation in Data Science: Data, the World, and You from University of Adelaide
A Hands-On Introduction to Process Mining from RWTH Aachen University
Basics of Data Science from RWTH Aachen University
Data-Driven Animation for Science Communication from University of California, Santa Cruz
Data Visualization from Ball State University
AI and Bioinformatics: Genomic Data Analysis from Taipei Medical University
[New] Data Analysis for Business from Fundação Instituto de Administração
Fundamentals of Business Problem Solving from Howard University
Business Modeling Tools from Howard University
Solving Business Problems with Spreadsheet Modeling from Howard University
[New] Data Preparation and Analysis from Illinois Institute of Technology
Text Mining for Marketing from O.P. Jindal Global University
Fundamental Skills in Bioinformatics from King Abdullah University of Science and Technology (KAUST)
Data Analysis for Business: Foundations from SDA Bocconi School of Management

Mathematics (32)

Linear Regression Modeling for Health Data from University of Michigan
Linear Algebra: Matrix Algebra, Determinants, & Eigenvectors from Johns Hopkins University
Linear Algebra: Linear Systems and Matrix Equations from Johns Hopkins University
Linear Algebra: Orthogonality and Diagonalization from Johns Hopkins University
Linear programming and its applications to computer science from Indian Institute of Technology Kanpur
Set Theory and Mathematical Logic from Indian Institute of Technology Kanpur
Advanced Course on Partial Differential Equations – II from Indian Institute of Science Bangalore
Introduction to Group Theory from Indian Institute of Science Bangalore
Introduction to Lie algebras from Indian Institute of Science Bangalore
Introduction to Statistics from IIT Hyderabad
Numerical Linear Algebra and Application from NPTEL
Mathematics of Waves: Visualized with Neural Networks from Purdue University
Resampling, Selection and Splines from University of Colorado Boulder
Regression Analysis from University of Colorado Boulder
[New] Introduction to optimization on smooth manifolds: first order methods from École Polytechnique Fédérale de Lausanne
Math Fundamentals: Algebra from Universitat Politècnica de València
Math Fundamentals: Integrals from Universitat Politècnica de València
Math Fundamentals: Numbers and Terminology from Universitat Politècnica de València
Math Fundamentals: Derivatives from Universitat Politècnica de València
[New] Maths Foundations from University of Adelaide
Introduction to Linear Algebra from The University of Sydney
Mathematical Techniques for Problem Solving in Engineering and Science from KU Leuven University
Algebra from Pondicherry University
Calculus from MES College of Engineering
Statistics for Business Decisions from CEC
An Introduction to Pre-University Mathematics from London School of Economics and Political Science
Model Diagnostics and Remedial Measures from Illinois Institute of Technology
Linear Regression from Illinois Institute of Technology
Variable Selection, Model Validation, Nonlinear Regression from Illinois Institute of Technology
[New] Statistical Learning from Illinois Institute of Technology
Basic Mathematics from Birla Institute Of Technology And Science–Pilani (BITS–Pilani)
Statistics Fundamentals for Business Analytics from Lehigh University

Art & Design (27)

Digital Case Method from Columbia University
Understanding the Value of Human-Centered Design from University of Illinois at Urbana-Champaign
Interior Design from Indian Institute of Technology Roorkee
Research Methodology for Planning and Architectural Studies from Indian Institute of Technology Roorkee
Discover Acting from University of London International Programmes
Using Rapid Prototyping in the Engineering Design Process from Arizona State University
Adding Electronics to Rapid Prototypes from Arizona State University
Rapid Prototyping Materials and Tooling from Arizona State University
Animation with JavaScript and jQuery from University of California, Davis
Evaluation for Arts, Culture, and Heritage: Principles and Practice from University of Leeds
Touring 101 for Musicians from Berklee College of Music
Building Your Career as a Professional Singer from Berklee College of Music
How to Make Money with Your Music Copyrights from Berklee College of Music
Introduction to Creative Thinking: Tools for Success from Imperial College London
Systematic Creative Thinking: Tools for Success from Imperial College London
Advanced Creative Thinking and AI: Tools for Success from Imperial College London
Arte, artesanía y creatividad sostenibles: tintas y tintes naturales from Universitat Politècnica de València
Introduction to German Opera from Dartmouth College
Introduction to Italian Opera from Dartmouth College
Reimaginar museos: Un nuevo futuro from University of Leicester
Akichi in Collections Management: Perspectives from a Japanese University Museum from Keio University
[New] Introduction to Modern Art from Taipei Medical University
Discovering Korean Music: The Spectrum of Sound from Hanyang University
Talon ka Soundarya Shastra from Doctor Harisingh Gour Vishwavidyalaya, Sagar
Korean Music, A Philosophical Exploration from Sungkyunkwan University
[New] Responsible Innovation and Circular Fashion from SDA Bocconi School of Management
[New] Circular Fashion Business Models from SDA Bocconi School of Management

Front End Developer Roadmap

Beau Carnes — Thu, 19 Oct 2023 14:23:48 +0000

Every week we publish a lot of great content on the freeCodeCamp.org YouTube channel. New people sometimes wonder where to start and what order to watch the courses. Well, if you want to become a front end developer, this is where to start.

We just released our front end developer learning path on the freeCodeCamp.org YouTube channel. We’ve curated a collection of top-notch courses on all of the key technologies you need to learn to become a front end developer. An you can watch them free on our channel. The full learning path is over 80 hours long.

In this article, we'll give a brief overview of the technologies you will learn as part of our front end developer learning path.

What is front end development?

Front end development (sometimes written "frontend development") is like designing the face of a website or app. It's all about how things look and feel when you use them. While back end developers make sure everything works behind the scenes, front end developers focus on what you see and interact with, making sure it's easy to use and looks good on any device. In short, front end developers turn designs into live websites and apps that people can use.

At its core, frontend development revolves around three main technologies: HTML, CSS, and JavaScript. We’ll explain more about these technologies in a bit, but for now just know that almost everything in frontend development revolves around them. As a frontend developer, your role is pivotal in ensuring that the website's design translates well to various devices, is user-friendly, and aligns with the client's vision.

How long does it take to become a Frontend Developer?

The journey to becoming a frontend developer is unique for everyone. For complete beginners, it might take anywhere between 6 to 12 months of dedicated learning and practice to land an entry-level position. For those with some prior knowledge, the timeline might be shorter. The key is consistent practice, engagement with the developer community, and continuous learning.

Should you learn everything covered in this learning path?

This frontend learning path covers a lot of important tools and technologies. Not every item on this roadmap is essential for entry into the field. Every job is unique and most of the jobs will require a subset of the technologies on the roadmap. The most important things to know are HTML, CSS, and JavaScript. But remember, the tech world is ever-evolving, and staying updated is crucial. This roadmap will help you identify areas you might need to explore further.

Essential Technologies for Frontend Development

So here are the essential technologies you need to learn. You can watch a full comprehensive course on each of these technologies, right on the freeCodeCamp.org YouTube channel as part of this front end learning path.

Internet Basics

The internet is a vast interconnected network that has revolutionized the way we communicate, work, and live. Before diving further into frontend development, it's essential to grasp the foundational concepts of how the internet functions.

This foundational knowledge encompasses understanding domains, the Domain Name System (DNS), servers, and protocols like HTTP/HTTPS. Additionally, a basic comprehension of web browsers, their role, and how they render web pages is crucial for anyone looking to venture into web development.

HTML

HTML, or HyperText Markup Language, is the cornerstone of web content. It's akin to the skeleton of a website, providing the essential structure upon which everything else is built.

As the standard markup language for web pages, HTML uses tags to define elements and structure the content. From headings to paragraphs, links, and images, everything visible on a webpage is typically structured using HTML.

Visual Studio Code

In the realm of code editors, Visual Studio Code (VSCode) stands out as a favorite among developers. It's more than just a simple editor; it's a powerful tool that makes coding efficient and enjoyable.

VSCode offers a bunch of features, including syntax highlighting, a range of extensions for added functionalities, and an integrated terminal. Its user-friendly interface and customization options have made it a go-to choice for many in the industry.

CSS

If HTML is the skeleton of a website, CSS, or Cascading Style Sheets, is its skin. It's responsible for the visual appeal of a website, dictating everything from colors and fonts to layouts.

CSS allows developers to create responsive designs that adapt to different screen sizes and devices. It ensures that websites are not only functional but also aesthetically pleasing and user-friendly.

JavaScript

JavaScript breathes life into static web pages. It's a dynamic programming language that introduces interactivity, making websites more engaging and user-centric.

From simple animations to complex functionalities like form validations and asynchronous data fetching, JavaScript plays a pivotal role. It's the magic behind the dynamic behavior of web applications.

Prompt Engineering

To maximize your productivity as a developer, it's important to understand how to use large language models, such as ChatGPT, Bard, and others. A knowledge of prompt engineering will help you understand how to get the most helpful responses from large language models.

And in case your wondering: yes, front end developers will still be needed in the future, even with technologies like ChatGPT. The workflow may be different, but there will be a human element required for the foreseeable future.

Version Control: Git and GitHub

In the world of software development, tracking and managing changes is crucial. This is where version control systems, particularly Git, come into play.

Git allows developers to track changes, collaborate seamlessly, and revert to previous versions if needed. GitHub, on the other hand, is a platform that hosts Git repositories, facilitating collaboration, code sharing, and even deployment.

Package Managers

As projects grow and evolve, managing software libraries and dependencies can become a challenge. Package managers are tools designed to address this challenge.

Popular package managers like npm or yarn help developers manage, install, and update software libraries seamlessly. They ensure that projects have the right versions of dependencies, making the development process smoother.

Bootstrap 5 and SASS

Designing responsive and visually appealing websites can be streamlined with the right tools. Bootstrap is one such framework that has revolutionized web design.

Bootstrap offers pre-designed components and a grid system, making responsive design a breeze. SASS, a CSS preprocessor, allows for advanced styling techniques, variables, and nested rules, enhancing the styling process.

JavaScript Frameworks (React, Vue, Angular, etc)

Modern web applications demand efficiency, scalability, and maintainability. JavaScript frameworks and libraries provide pre-written code to support these requirements.

Frameworks like React, Vue, and Angular have their own philosophies and methodologies but aim to simplify complex tasks, promote code reusability, and enhance performance. They play a pivotal role in building single-page applications and dynamic web apps.

Tailwind CSS

Tailwind CSS has emerged as a game-changer in the world of CSS frameworks. It adopts a utility-first approach, allowing for rapid UI development.

Instead of predefined components, Tailwind provides utility classes that can be combined to create custom designs. This approach promotes flexibility and reduces the need for custom CSS, leading to faster development cycles.

Build Tools (Vite, etc)

As web applications become more complex, the need for efficient build tools becomes evident. These tools optimize, bundle, and serve our code, ensuring that applications run smoothly.

Vite, for instance, is a next-generation frontend tooling solution that offers faster build times. Such tools handle tasks like transpilation, minification, and module bundling, ensuring that the code is optimized for production.

Testing JavaScript (Jest, Cypress)

Ensuring the reliability and functionality of web applications is paramount. This is where JavaScript testing tools come into play.

Tools like Jest, designed for unit testing, and Cypress, tailored for end-to-end testing, help developers ensure that their code functions as intended. Regular testing minimizes bugs and enhances the overall quality of web applications.

TypeScript

While JavaScript is dynamic and flexible, there are scenarios where a more structured approach is beneficial. Enter TypeScript, a superset of JavaScript that introduces static typing.

TypeScript offers type annotations, interfaces, and enhanced tooling, leading to more robust code. It helps catch errors during compile-time, ensuring that potential issues are addressed before runtime.

Web Security (OWASP)

In today's digital age, web security is of utmost importance. Protecting user data and ensuring the integrity of web applications is a top priority.

The Open Web Application Security Project (OWASP) provides guidelines and best practices to ensure web application security. Familiarizing oneself with common vulnerabilities and their mitigations is essential for any frontend developer.

GraphQL

Traditional RESTful APIs come with limitations, especially when dealing with complex data structures. GraphQL emerges as a powerful alternative, offering more flexibility in querying data.

GraphQL allows clients to request only the data they need, reducing over-fetching. It provides a more efficient, powerful, and flexible alternative to the traditional REST API.

Next.js

Building server-rendered React applications can be streamlined with the right framework. Next.js is a leading choice, offering features that enhance performance and developer experience.

Next.js provides automatic code splitting, server-side rendering, and a rich set of features that make building scalable React applications a breeze.

Astro

In the quest for optimal performance, new frameworks like Astro are pushing the boundaries. Astro introduces a unique approach to building faster websites.

Astro allows developers to deliver less JavaScript by default, resulting in faster load times. It offers partial hydration and integrates with various modern frameworks, ensuring flexibility and performance.

Performance Best Practices

A well-designed website is not just about aesthetics; performance plays a crucial role in user experience and search engine rankings.

Adhering to best practices like optimizing images, leveraging browser caching, and minimizing server response times can significantly boost website performance. Regular audits using tools like Google's Lighthouse can provide insights and recommendations.

React Native

The world is increasingly mobile, and developers need tools to build cross-platform mobile applications efficiently. React Native is a framework that allows for the development of native mobile apps using React.

With React Native, developers can write most of their application's code once and run it on both iOS and Android. It offers a rich set of components and native modules, ensuring that apps feel truly native.

Conclusion

Front end development is a dynamic and ever-evolving field. As technologies emerge and best practices evolve, staying updated and adaptable is key. This roadmap provides a foundation, but the journey of learning and exploration is endless. Engage with the community, experiment with new tools, and always strive for excellence. The world of front end development offers endless possibilities, and with the right tools and knowledge, you can craft exceptional web experiences.

Watch the learning path on the freeCodeCamp.org YouTube channel (>85 hours long).

Intro to Generative AI – 10 Free Courses by Google

Eamonn Cottrell — Thu, 22 Jun 2023 22:22:52 +0000

Are you tired of all the AI talk yet?

I am too, but I'm also intrigued by the technology behind it.

If you'd like to dive into some of the details behind how AI actually works and take a break from the many creepy AI examples on the internet, check this out:

Google has released a free set of training courses for generative AI. Here's their announcement post.

Picture for generative AI courses

Video Walkthrough

I've made a short video of the coursework if you'd prefer a visual walkthrough of my first impressions:

Overview

There are 10 courses in this free learning path. Many are aimed at beginners with no prerequisite knowledge. Some suggest a background in Python, SQL, and/or machine learning. All of them deliver content through a combination of videos, articles, labs and quizzes.

There are badges to show that you've completed them, and I'm happy to see a freely available set of courses around the technology behind AI.

Screenshot of Google course badge

The amount of content produced by and highlighting AI is overwhelming right now, but it's a safe bet that this is going to stick around. As such, it's best to arm yourselves with as much information about it as you can so that you can responsibly create tools and content for the future.

Courses Material

I've created a Google Sheet with all the course info pulled from each of these courses. Check it out here. Google has done a fine job of creating a brief FAQ for each of the courses, and I've pulled them all into one sheet for easy comparison.

Screenshot of Google Sheet summary of all courses

Inside each course, you'll be presented with a straightforward navigation for the content. It's broken into video instruction, a curated collection of readings to peruse, and quizzes. Some courses also have online labs to complete in a certain amount of time.

Video content for the Create Image Captioning Models course

The curated list of readings is quite comprehensive, and you could easily exceed the estimated 45 minutes of time to complete the modules if you read through every one. But it is nice to have such a large list of resources compiled in one place.

The list of readings for the Intro to Large Language Models course

There are also Labs hosted in some of the courses. If you've taken any of Google's Coursera courses, you'll be familiar with this delivery method. You're given a handful of tasks and a countdown timer, in this case 1hr, will begin when you start the lab.

Screenshot of lab work

Here is the full list of courses:

Introduction to Generative AI – designed to be an overview of what generative AI is and how it differs from machine learning methods.
Introduction to Large Language Models – explores what large language models are, where they are used, and how to use prompt tuning. (If you haven't noticed, prompt writing is being touted as a skill of the future right now.)
Introduction to Responsible AI – an ethical course on what responsible AI is, how it's implemented in Google products, and why it's important. This course introduces Google's 7 AI Principles. I didn't know this was a thing, but there's a whole page devoted to it. Covering topics from social responsibility, to safety, accountability and privacy design principles, I was happy to see that there is large effort being paid to build in solid principles.
Generative AI Fundamentals – A quiz covering topics from the first three courses.
Introduction to Image Generation – An introduction to diffusion models which are a family of models used in image generation. Some pre-existing knowledge of machine learning, deep learning, convolutional neural nets and/or Python programming is suggested.
Encoder-Decoder Architecture – overview of a machine learning architecture for tasks like machine translation, text summarization, and question answering. Python and Tensorflow knowledge is suggested as a prerequisite.
Attention Mechanism – a technique that allows neural networks to focus on specific parts of an input sequence. Some pre-existing knowledge of machine learning, deep learning, natural language processing, and/or Python programming is suggested.
Transformer Models and BERT Model – Bidirectional Encoder Representations from Transformers...this is what BERT stands for in case you didn't know. You'll learn the main components of the Transformer architecture and intermediate machine learning experience as well, and knowledge of Python and TensorFlow are recommended.
Create Image Captioning Models – how to create an image captioning model using deep learning. Deep learning, machine learning, natural language processing, computer vision and Python are recommended prerequisites.
Introduction to Generative AI Studio – you'll walk through demos of the Generative AI Studio which helps prototype and customize generative AI models. There is a hands-on lab at the end.

My Thoughts

After spending some time browsing through all of these courses, it's a nice mix of truly beginner-friendly content and some intermediate level stuff that requires previous knowledge of machine learning, Python, deep learning, and/or natural language processing.

I appreciate how there are answers to many common questions in the drop down menus for each course (and I've compiled all of those in one place in this Google Sheet).

Screenshot of Google Cloud certifications

This is a great starting point if you are truly interested in the inner-workings of AI. It also looks to be a potential on-ramp to some of Google Cloud's larger certifications as there are links to further training sprinkled in the courses.

What do you think?

👋My name is Eamonn Cottrell, and I'm building content around Google Sheets & Workspace.

Get my 📨 newsletter here. Find me on 📺 YouTube here.

Please ask questions in the comments, or send me a message; I love making new spreadsheet connections!

Learn Git and GitHub in Spanish – Course for Beginners

Estefania Cassingena Navone — Thu, 09 Feb 2023 15:25:52 +0000

Hi! If you speak Spanish and you want to learn Git and GitHub, you are in the right place.

In this article, you will find a brief introduction to Git and GitHub. You will learn why they are very powerful tools and why you should learn them if your goal is to be a developer.

Then, you will find a 5+ hour Git and GitHub course on freeCodeCamp's Spanish YouTube channel where you can learn the fundamentals in Spanish with practical examples and projects.

If you have Spanish-speaking friends, you are welcome to share the Spanish version of this article with them.

Let's begin! ✨

🔸 What is Version Control?

First, let's see what version control is because this concept is essential for Git and GitHub.

Haven't you ever wished that you could track the changes you have made to a project or even go back to a previous version of a file?

Let me tell you that this is possible with version control.

With a version control system, you can keep track of the changes you make to your files and keep multiple versions of your project on the same computer simultaneously. This way, you can switch between different versions of your project as you make changes and create new features.

That is the power of version control.

You can keep an "experimental" version of your project to work on a new feature while you also have the stable version of your project live for your users.

Two of the most popular version control tools in the global developer community are Git and GitHub. Let's start with a brief overview of Git.

🔹 What is Git?

Git is one of the most popular version control systems among the developer community. I promise you that learning Git will be totally worth your time if your goal is to be a software developer.

Git (official logo).

With Git, you can track the changes you make to your files and work with different versions of your project on the same computer.

By learning a few important Git commands, you can focus on your software development projects while Git takes care of the internal details of all the important version control tasks.

◼️ Basic Git Concepts

Now that you know what Git is, let's see some concepts that are essential for working with Git:

Git Repository

A repository is where Git stores our project files and tracks their different versions. A repository can be either local or remote.

A local repository is stored locally on your computer. A remote repository is stored remotely on the servers of the hosting service of your choice (like, for example, GitHub).

Working directory

The working directory is the directory of the project in our file system where the files are stored. This is, for example, the folder that you open in your code editor or IDE to work with your files.

Staging area

The staging area contains the set of files and changes that will be included in the next commit (a record of the changes made to the repository). We can add and remove files from this area if we need to.

Commit

A commit is like a "snapshot" of your project at a particular moment in time. A commit records changes that have been made to the project. You choose when to create a commit and what to include in that commit.

💡 Tip: To describe the changes recorded in a commit, we write a commit message that we can check later on as we work on the project.

Branch

A branch is an independent line of development of a project tracked by Git. Every project starts with a default branch that we usually call **main**. We can create a new branch to work on a new feature without affecting the main version of our project.

Merge

We can also combine (merge) branches when we need to incorporate the changes that have been made on one branch into another another. This is what we usually do when a new feature is ready to be added to the live version of our project.

These are fundamental concepts for working with Git. Now let's see the actual command-line tool that we will work with.

◼️ Git Bash

During the course, we will use Git Bash, a command-line tool for Windows that provides an environment where we can run Git commands.

💡 Tip: Bash stands for Bourne Again Shell. A bash is an application used to interact with the operating system of a computer through commands.

Screenshot of Git Bash (Windows)

Great! Now that you know more about Git, let's start diving into the basics of GitHub. Git and GitHub work together to create the workflow that software developers use every day.

🔸 What is GitHub?

GitHub's Official Homepage

When you work with Git, everything you store on your repository is only stored locally. Only you can have access to your repository and to your changes.

This can be exactly what you need if you are working on a personal project.

However, if you are part of a team, you will need to collaborate with other developers to modify the same codebase, which can be very problematic if there is no way to have quick access to the changes made by other developers.

This is where GitHub comes to the rescue!

When you create a GitHub repository, all the members of the team have access to this repository. They can create local copies (clones) of the remote repository on their computers.

These clones are super helpful because developers can work with the files locally, make changes and commits, and send them back to GitHub.

When the remote repository receives new changes, team members can also incorporate these changes into their local repositories to make sure that there are no conflicts between their changes and the changes made by their colleagues.

That is the power of Git and GitHub. Now let's see some data on why you should learn Git and GitHub if your goal is to be a developer.

🔹 Why Should You Learn Git and GitHub?

Git and GitHub are used widely across many different fields and organizations.

💡 Tip: At freeCodeCamp, we use Git and GitHub to maintain and update the live version of the learning platform that you can see and use every day.

Git's official website also mentions that these companies and projects use Git:

Google
Microsoft
Twitter
LinkedIn
Netflix
PostgreSQL
Android
Linux
Ruby on Rails
Gnome
Eclipse

According to the Stack Overflow Developer Survey 2022:

No other technology is as widely used as Git. Especially among Professional Developers.

The results are very consistent. 93.87% of the 71,379 developers who answered this question on the survey use Git as their version control system.

The results of the Stack Overflow Developer Survey 2022 for the category Version control systems. 93.87% of the respondents chose Git as their version control system.

In addition to being a very valuable tool in real-world scenarios, Git is also one of the most popular version control systems in the community of learners who are learning how to code.

Among the respondents who are learning how to code, 81.87% of them use Git.

The results of the Stack Overflow Developer Survey 2022 for the category Version control systems. 81.87% of the respondents who are learning how to code use Git.

Based on these results, you can see that Git is a very powerful tool for software developers from all background and levels of experience.

When you combine the power of Git with the power of GitHub, you unlock the true power of version control.

For example, freeCodeCamp's repository is an open-source project hosted on GitHub.

freeCodeCamp's GitHub repository

GitHub's official website also mentions that the following organizations host their repositories on GitHub:

Stripe
Pinterest
KPMG
Mercedes-Benz
Procter & Gamble
Telus

According to the Stack Overflow Developer Survey 2022:

GitHub is the most popular Version Control for both personal and professional use.

In this survey, GitHub was the most popular version control platform among the developer community.

The results of the Stack Overflow Developer Survey 2022 for the Version control platforms category.

Another great thing about GitHub for learners who are learning how to code is that every profile has a calendar for tracking contributions. This is an interactive calendar with one small square per day.

If you made more contributions on a particular day, you will see a darker shade of green on its corresponding square.

Contributions calendar from this article by GitHub.

This interactive calendar is frequently used by recruiters to evaluate your experience, projects, and contributions.

When you are actively contributing to projects hosted on GitHub, you create a timeline of contributions that recruiters can review to see how you communicate with other developers and how you face challenges.

Basically, when you contribute on GitHub, you are gradually creating your developer portfolio while you also acquire experience with real-world projects.

Great! Now that you know what Git and GitHub are, and why you should learn, them, let's dive into the course content.

🔸 Course Content

This is a brief outline of the topics that you will learn during the course. By the end of the course, you will be able to work with Git and GitHub on your personal and professional projects.

We will working with text files and simple code files, so you can take this course regardless of the programming language(s) that you have learned so far or even if you are just starting to dive into the amazing world of programming.

💡 Tip: My goal is to teach you the Git and GitHub workflow step by step in a way that will be completely independent from the content of the files. This way, you will be able to apply your knowledge to any coding project.

Introduction to Git

What is Git? Real-life applications.
Concept of a repository.
How to install Git and Git Bash.
Git Bash Commands.
Configure Git username and email.

Git Repositories

How to create a Git repository.
Working directory.
Staging area.
**.git** directory.
The **git status** command.

Git Commits

What is a commit?
How to create a commit.
Show commit history with **git log**.
Configure a Git editor (Visual Studio Code).
Amend the most recent commit.
Undo a commit.

Branches

What is a branch?
How to create a branch.
The **main** branch.
Checkout a branch.
Rename a branch.
Delete a branch.
Create commits on a branch.
See commit history on a branch.

Merging Branches

What is merging?
How to merge two branches.
Merge conflicts.
How to delete a branch after merging it with **main**.

Introduction to GitHub

What is GitHub?
Create your account and profile.
Customize repository settings.
Rename a repository.
Delete a repository.

Git and GitHub Workflow

Clone a repository.
Send (push) changes to GitHub.
Receive (pull) changes from GitHub.
HTTPS validation for pushing changes.
**git pull** vs. **git fetch**
Fork a repository.
Clone a forked repository.
What is a pull request?
Start and submit a pull request.
Update a forked repository.
What is an issue?
How to open an issue.
Issue templates.
Labels for issues and pull requests.
Clone new remote branches to a local repository.
Delete remote and local branches.

We will see how these principles and elements work on a real project: freeCodeCamp's GitHub repository.

freeCodeCamp's GitHub repository

We will also create small projects as you learn these topics step by step.

📌 Git and GitHub Course

Awesome. Now that you know more about Git and GitHub and what you will learn during the course, you are welcome to start taking the course in Spanish:

✍️ Course created by Estefania Cassingena Navone. Check out my YouTube channel (Coding with Estefania) and Twitter @EstefaniaCassN.

I really hope you like the course and find it helpful to take your first steps into the world of version control.

You are also welcome to continue learning with our other Spanish courses:

860+ Free Online Programming & Computer Science Courses You Can Start This New Year

freeCodeCamp — Wed, 04 Jan 2023 17:00:00 +0000

By Dhawal Shah

Twelve years ago, universities like Stanford and MIT opened up free online courses to the public. Today, over 1,200 schools around the world have created thousands of free online courses.

To welcome the new year, I’ve compiled this list of 860+ such free online courses that you can start right now. For this, I leveraged Class Central’s database of over 100,000 online courses. When available, I've also included the course average rating.

Class Central homepage

I’ve sorted these courses into the following categories, based on their difficulty level:

Beginner
Intermediate
Advanced

Courses that are being offered for the first time are marked as [NEW]. Almost all of these courses are completely self-paced, meaning you can start right now.

You can find complete lists of technology-related courses on Class Central’s Computer Science, Data Science, and Programming subject pages. If the options feels overwhelming, there, you'll also find guides to help you find the best course for you.

Finally, if you have trouble figuring out how to sign up for Coursera courses for free, don’t worry — I’ve written an article on how to do that, too.

Beginner (225)

Elements of AI from University of Helsinki ★★★★★(713)
Unlocking Information Security I: From Cryptography to Buffer Overflows from Tel Aviv University ★★★★★(298)
CS50's Introduction to Computer Science from Harvard University ★★★★★(140)
Computational Social Science Methods from University of California, Davis ★★★★★(107)
Introduction to HTML5 from University of Michigan ★★★★☆(50)
Unlocking Information Security II: An Internet Perspective from Tel Aviv University ★★★★★(50)
Internet History, Technology, and Security from University of Michigan ★★★★★(41)
Introduction to Linux from Linux Foundation ★★★★☆(37)
Introduction to Databases from Stanford University ★★★★★(30)
Build a Modern Computer from First Principles: From Nand to Tetris (Project-Centered Course) from Hebrew University of Jerusalem ★★★★★(28)
Fundamentos TIC para profesionales de negocios: Desarrollo de Software from Universitat Politècnica de València ★★★★☆(26)
[New] Introduction to Quantum Computing from The University of British Columbia
[New] Coding Interview Preparation from Meta
[New] Software Development Practices from Meta
Introduction to Cyber Security from The Open University ★★★★☆(22)
Web Security Fundamentals from KU Leuven University ★★★★☆(22)
CS50's Web Programming with Python and JavaScript from Harvard University ★★★★★(21)
HTML, CSS, and Javascript for Web Developers from Johns Hopkins University ★★★★★(20)
Computer Science 101 from Stanford University ★★★★☆(18)
Programming Basics from Indian Institute of Technology Bombay ★★★☆☆(18)
Diagramas UML estructurales para la Ingeniería del Software from Universitat Politècnica de València ★★★★★(17)
Fundamentos TIC para profesionales de negocios: Aplicaciones empresariales from Universitat Politècnica de València ★★★★★(16)
Introduction to Networking from New York University (NYU) ★★★★☆(16)
Introduction to CSS3 from University of Michigan ★★★★★(14)
CS50's Computer Science for Business Professionals from Harvard University ★★★★★(13)
Getting Started with AWS Machine Learning from Amazon Web Services ★★★★☆(13)
Building AI from University of Helsinki ★★★★☆(13)
Introduction to the Internet of Things and Embedded Systems from University of California, Irvine ★★★★☆(12)
CS50's Introduction to Artificial Intelligence with Python from Harvard University ★★★★★(11)
Creative Programming for Digital Media & Mobile Apps from University of London International Programmes ★★★★☆(11)
HTML5 Coding Essentials and Best Practices from World Wide Web Consortium (W3C) ★★★★☆(11)
CS50's Understanding Technology from Harvard University ★★★★★(10)
Technical Support Fundamentals from Google ★★★★☆(10)
Learn to Program: Crafting Quality Code from University of Toronto ★★★★☆(9)
Usable Security from University of Maryland, College Park ★★★☆☆(9)
Computer Hardware and Operating Systems from New York University (NYU) ★★★★★(9)
Linux Command Line Basics
Intro to Relational Databases
How To Create a Website in a Weekend! (Project-Centered Course) from State University of New York ★★★★☆(7)
Introducción a la programación en C: Instrucciones de control y ficheros de texto from Universidad Autónoma de Madrid ★★★★★(7)
AI For Everyone from DeepLearning.AI ★★★★★(6)
CS50's Computer Science for Lawyers from Harvard University ★★★★★(5)
Introduction to Computing using Python from Georgia Institute of Technology ★★★★★(5)
Introduction to the Internet of Things from Universitat Politècnica de València ★★★★☆(5)
Paradigms of Computer Programming – Fundamentals from Université catholique de Louvain ★★★★★(5)
Paradigms of Computer Programming – Abstraction and Concurrency from Université catholique de Louvain ★★★★☆(5)
Web Coding Fundamentals: HTML, CSS and Javascript from National University of Singapore ★★★★★(5)
The Computing Technology Inside Your Smartphone from Cornell University ★★★★★(5)
Basics of Computing and Programming from New York University (NYU) ★★★★☆(5)
C for Everyone: Programming Fundamentals from University of California, Santa Cruz ★★★★☆(5)
Programming in Scratch from Harvey Mudd College ★★★★★(5)
Web Applications for Everybody
Problem Solving, Python Programming, and Video Games from University of Alberta ★★★★☆(4)
Full Stack open 2022 from University of Helsinki ★★★★★(4)
CS For All: Introduction to Computer Science and Python Programming from Harvey Mudd College ★★★★★(4)
CS50's Introduction to Game Development from Harvard University ★★★★☆(3)
How Computers Work from University of London International Programmes ★★★★☆(3)
Introduction to Web Development from University of California, Davis ★★★★☆(3)
Python Programming Essentials from Rice University ★★★★★(3)
Web Development and Design using Wordpress from California Institute of the Arts ★★★★☆(3)
Object-Oriented Programming from Indian Institute of Technology Bombay ★★★☆☆(3)
C Programming: Modular Programming and Memory Management from Dartmouth College ★★★☆☆(3)
Introduction to Structured Query Language (SQL) from University of Michigan ★★★★☆(2)
The Beauty and Joy of Computing - AP® CS Principles Part 1 from University of California, Berkeley ★★★★★(2)
Introduction to Accounting Data Analytics and Visualization from University of Illinois at Urbana-Champaign ★★★★★(2)
Software Engineering: Introduction from The University of British Columbia ★★★☆☆(2)
Web Design: Strategy and Information Architecture from California Institute of the Arts ★★★★★(2)
Introduction to Software Testing from University of Minnesota ★★★★★(2)
TCP/IP and Advanced Topics from University of Colorado System ★★★★☆(2)
Introduction to Cybersecurity for Business from University of Colorado System ★★★★★(2)
Introduzione all'informatica from University of Naples Federico II ★★★★★(2)
Introduction to the Internet of Things (IoT) from Curtin University ★★★☆☆(2)
C Programming: Pointers and Memory Management from Dartmouth College ★★★★★(2)
C Programming: Language Foundations from Dartmouth College ★★★★★(2)
Linux Basics: The Command Line Interface from Dartmouth College ★★★★★(2)
C Programming: Using Linux Tools and Libraries from Dartmouth College ★★★★★(2)
Think. Create. Code from University of Adelaide ★★★★★(2)
Introduction to HTML and JavaScript from Microsoft ★★★★★(2)
Introduction to NodeJS from Microsoft ★★★★★(2)
Introduction to Database Queries from New York University (NYU) ★★★★★(2)
Software Engineering Essentials from Technische Universität München (Technical University of Munich) ★★★★☆(2)
Introducción a la programación en Python I: Aprendiendo a programar con Python from Pontificia Universidad Católica de Chile ★★★★★(2)
MongoDB Basics
CS50's AP® Computer Science Principles from Harvard University ★★★★★(1)
CS50's Mobile App Development with React Native from Harvard University ★★★★☆(1)
Databases: JSON Data from Stanford University ★☆☆☆☆(1)
Building Database Applications in PHP from University of Michigan ★★★★★(1)
Building Web Applications in Django from University of Michigan ★★★★★(1)
Computer Science: Programming with a Purpose from Princeton University ★★★★★(1)
Introduction to Computer Programming from University of London International Programmes ★★★★★(1)
Cyber Security Fundamentals from University of London International Programmes ★★★★★(1)
Principles of Secure Coding from University of California, Davis ★★★★★(1)
Python Data Visualization from Rice University ★★★★★(1)
Programming with Scratch from The Hong Kong University of Science and Technology ★★☆☆☆(1)
Cyber Security Economics from Delft University of Technology ★★☆☆☆(1)
Proactive Computer Security from University of Colorado System ★★★★★(1)
Introduction à la programmation orientée objet (en Java) from École Polytechnique Fédérale de Lausanne ★★★★★(1)
NoSQL Databases from University of Maryland, Baltimore County ★★☆☆☆(1)
Introduction to TCP/IP from Yonsei University ★★★★★(1)
Introdução à Ciência da Computação com Python Parte 1 from Universidade de São Paulo ★★★★★(1)
Writing Professional Code from Microsoft ★☆☆☆☆(1)
AI for Everyone: Master the Basics from IBM ★★★★★(1)
Introduction to Cloud Computing from IBM ★★★★★(1)
Introduction to Cyber Attacks from New York University (NYU) ★★★★★(1)
Lernen objekt-orientierter Programmierung from Technische Universität München (Technical University of Munich) ★★★★★(1)
Computing Form and Shape: Python Programming with the Rhinoscript Library from Rhode Island School of Design ★★★★★(1)
MyCS: Computer Science for Beginners from Harvey Mudd College ★★★☆☆(1)
Diseño Web con HTML5 + CSS from Universitas Telefónica ★☆☆☆☆(1)
Data Privacy Fundamentals from Northeastern University ★★★★★(1)
ES6 - JavaScript Improved
Applications of TinyML from Harvard University
Deploying TinyML from Harvard University
Databases: Unified Modeling Language from Stanford University
Databases: Indexes and Transactions from Stanford University
Databases: On-Line Analytical Processing from Stanford University
Databases: OLAP and Recursion from Stanford University
Databases: Semistructured Data from Stanford University
Databases: Modeling and Theory from Stanford University
Hacker Tools from Massachusetts Institute of Technology
Understanding the World Through Data from Massachusetts Institute of Technology
Computational Thinking for Problem Solving from University of Pennsylvania
AI Fundamentals for Non-Data Scientists from University of Pennsylvania
Django Features and Libraries from University of Michigan
Web Application Technologies and Django from University of Michigan
Web Application Technologies and Django from University of Michigan
Database Architecture, Scale, and NoSQL with Elasticsearch from University of Michigan
The Power of Object-Oriented Programming from University of Michigan
Introduction to DevSecOps from Johns Hopkins University
The Blockchain System from University of California, Irvine
Data, Security, and Privacy from University of California, Irvine
Productivity and Systems Development from University of California, Irvine
The Nature of Data and Relational Database Design from University of California, Irvine
The Beauty and Joy of Computing (CS Principles), Part 1 from University of California, Berkeley
The Beauty and Joy of Computing - AP® CS Principles Part 2 from University of California, Berkeley
The Beauty and Joy of Computing (CS Principles), Part 4 from University of California, Berkeley
The Beauty and Joy of Computing (CS Principles), Part 3 from University of California, Berkeley
Programming Fundamentals from Duke University
Interacting with the System and Managing Memory from Duke University
Introduction to Programming and Animation with Alice from Duke University
Cloud Computing Foundations from Duke University
Human Factors in AI from Duke University
Big Data Analytics in Healthcare from Georgia Institute of Technology
Data Analysis and Visualization from Georgia Institute of Technology
Introduction to Cybersecurity from University of Washington
Introduction to Internationalization and Localization from University of Washington
Applied Analytics and Data for Decision Making from University at Buffalo
Building Interactive 3D Characters and Social VR from University of London International Programmes
Coding for Designers, Managers, & Entrepreneurs I from University of Virginia
Coding for Designers, Managers, & Entrepreneurs II from University of Virginia
Coding for Designers, Managers, & Entrepreneurs III from University of Virginia
Artificial Intelligence in Marketing from University of Virginia
Identifying Security Vulnerabilities from University of California, Davis
Evidence and Data Collection for Problem Solving from University of Leeds
Python Data Analysis from Rice University
Введение в базы данных from St. Petersburg State Polytechnic University
Cloud Security Basics from University of Minnesota
Foundations of Data Analytics from The Hong Kong University of Science and Technology
AP Computer Science A: Java Programming Classes and Objects from Purdue University
AP Computer Science A: Java Programming Loops and Data Structures from Purdue University
AP Computer Science A: Java Programming Polymorphism and Advanced Data Structures from Purdue University
Cybersecurity for Everyone from University of Maryland, College Park
What is “the mind” and what is artificial intelligence? from University of Colorado Boulder
Cybersecurity for Data Science from University of Colorado Boulder
Trees and Graphs: Basics from University of Colorado Boulder
Data Science as a Field from University of Colorado Boulder
Fundamentals of Data Visualization from University of Colorado Boulder
Relational Database Design from University of Colorado Boulder
Scratch: Programmeren voor kinderen (8+) from Delft University of Technology
AI in Practice: Preparing for AI from Delft University of Technology
AI in Practice: Applying AI from Delft University of Technology
Software Design Methods and Tools from University of Colorado System
Software Design as an Element of the Software Development Lifecycle from University of Colorado System
Software Design as an Abstraction from University of Colorado System
Shell Programming - A necessity for all Programmers from Indian Institute of Technology Bombay
Basi di dati from University of Naples Federico II
Programmazione I from University of Naples Federico II
Foundations of Data Science from Indian Institute of Management Bangalore
Relational Database Design from University System of Maryland
Relational Database Management Systems from University System of Maryland
Video Game Design and Balance from Rochester Institute of Technology
Deep Learning for Business from Yonsei University
Technologies and platforms for Artificial Intelligence from Politecnico di Milano
Cyber Security Basics: A Hands-on Approach from Universidad Carlos iii de Madrid
Introducción a UML from Universidad de los Andes
Web of Data from EIT Digital
Blockchain for the decision maker from EIT Digital
C Programming: Getting Started from Dartmouth College
C Programming: Advanced Data Types from Dartmouth College
Diseñando páginas web con Bootstrap 4 from Universidad Austral
Introdução à Ciência da Computação com Python Parte 2 from Universidade de São Paulo
Introduction to Design Thinking from Microsoft
AI Fundamentals from Microsoft
Introduction to Web Development with HTML5, CSS3, and JavaScript from IBM
NoSQL Database Basics from IBM
Relational Database Administration (DBA) from IBM
Introduction to Web Development with HTML, CSS, JavaScript from IBM
Introduction to DevOps from IBM
Cyber Attack Countermeasures from New York University (NYU)
Information Security - Authentication and Access Control from New York University (NYU)
Penetration Testing - Exploitation from New York University (NYU)
A Beginner’s Guide to Becoming a Blockchain Developer with Overledger from King's College London
Introduction to Quantum Computing for Everyone from The University of Chicago
Introduction to Quantum Computing for Everyone 2 from The University of Chicago
Machine Learning: Concepts and Applications from The University of Chicago
Introduction to Blockchain Technology and Applications from University College London
Introduction to Open Source Networking Technologies from Linux Foundation
Data and AI Fundamentals from Linux Foundation
Programming Languages Ⅰ from Korea Advanced Institute of Science and Technology
Programming Languages Ⅱ from Korea Advanced Institute of Science and Technology
C for Everyone: Structured Programming from University of California, Santa Cruz
Data Visualization for All from Trinity College
Mobile Computing with App Inventor – CS Principles from The University of Warwick
プログラミングしながら学ぶコンピュータサイエンス入門 : Introduction to Computer Science and Programming from Tokyo Institute of Technology
Introduction to Computer Science and Programming from Tokyo Institute of Technology
Understanding Quantum Computers from Keio University
DevOps with Kubernetes from University of Helsinki
DevOps with Docker from University of Helsinki
Programming with GUIs from Raspberry Pi Foundation
Programming 102: Think Like a Computer Scientist from Raspberry Pi Foundation
Machine Learning Basics from Sungkyunkwan University
Introduction to MongoDB from MongoDB University
Programación Orientada a Objetos (POO) from MéxicoX
Information Technology Foundations from Western Governors University
Scripting and Programming Foundations from Western Governors University
HTTP & Web Servers

Intermediate (457)

Using Databases with Python from University of Michigan ★★★★★(4060)
R Programming from Johns Hopkins University ★★★☆☆(246)
The Data Scientist’s Toolbox from Johns Hopkins University ★★★☆☆(166)
Machine Learning for Musicians and Artists from Goldsmiths University of London ★★★★★(89)
Divide and Conquer, Sorting and Searching, and Randomized Algorithms from Stanford University ★★★★★(68)
Functional Programming Principles in Scala from École Polytechnique Fédérale de Lausanne ★★★★★(66)
Data Science and Agile Systems for Product Management from University System of Maryland ★★★★★(62)
Algorithms, Part I from Princeton University ★★★★★(59)
Getting and Cleaning Data from Johns Hopkins University ★★★☆☆(57)
Cryptography I from Stanford University ★★★★★(53)
Intelligenza Artificiale from University of Urbino ★★★★★(49)
Python for Data Science from University of California, San Diego ★★★★☆(47)
Introduction to Data Science in Python from University of Michigan ★★☆☆☆(46)
Object-Oriented Design from University of Alberta ★★★★☆(39)
Introduction to Big Data from University of California, San Diego ★★★☆☆(35)
Making Sense of Data in the Media from The University of Sheffield ★★★★★(35)
Statistical Inference from Johns Hopkins University ★★★☆☆(34)
Regression Models from Johns Hopkins University ★★★☆☆(34)
Probability and Statistics in Data Science using Python from University of California, San Diego ★★☆☆☆(31)
CS188.1x: Artificial Intelligence from University of California, Berkeley ★★★★★(30)
Principles of Computing (Part 1) from Rice University ★★★★★(30)
Reproducible Research from Johns Hopkins University ★★★★☆(27)
Practical Machine Learning from Johns Hopkins University ★★★☆☆(27)
Programming Languages, Part A from University of Washington ★★★★★(27)
Responsive Website Basics: Code with HTML, CSS, and JavaScript from University of London International Programmes ★★★★☆(27)
Mining Massive Datasets from Stanford University ★★★★★(25)
A Crash Course in Data Science from Johns Hopkins University ★★★★☆(25)
Design Patterns from University of Alberta ★★★★★(25)
Software Security from University of Maryland, College Park ★★★★☆(24)
Algorithmic Toolbox from University of California, San Diego ★★★★☆(23)
Introducción a la Inteligencia Artificial: Principales Algoritmos from Galileo University ★★★★★(22)
Algorithms, Part II from Princeton University ★★★★★(21)
Cloud Computing Concepts, Part 1 from University of Illinois at Urbana-Champaign ★★★☆☆(21)
Data Visualization from University of Illinois at Urbana-Champaign ★★★☆☆(21)
Learning From Data (Introductory Machine Learning) from California Institute of Technology ★★★★★(21)
Statistics and R from Harvard University ★★★★☆(20)
Automata Theory from Stanford University ★★★★☆(20)
Introduction to Machine Learning Course from Stanford University ★★★★☆(20)
Data Analysis with R from Facebook ★★★★★(18)
MongoDB for Java Developers
Process Mining: Data science in Action from Eindhoven University of Technology ★★★★☆(17)
Data Structures from University of California, San Diego ★★★★☆(16)
Principles of Computing (Part 2) from Rice University ★★★★☆(16)
Software Architecture from University of Alberta ★★★★☆(16)
How to Code: Simple Data from The University of British Columbia ★★★★☆(15)
Algorithmic Thinking (Part 1) from Rice University ★★★★☆(15)
The Nature of Code from Processing Foundation ★★★★★(15)
Design of Computer Programs from Stanford University ★★★★☆(14)
Python for Genomic Data Science from Johns Hopkins University ★★★☆☆(14)
Building a Data Science Team from Johns Hopkins University ★★★★☆(14)
Text Retrieval and Search Engines from University of Illinois at Urbana-Champaign ★★★☆☆(14)
Responsive Web Design from University of London International Programmes ★★★★☆(14)
Data Analysis: Take It to the MAX() from Delft University of Technology ★★★☆☆(13)
Intro to Data Science
Using Python for Research from Harvard University ★★★★☆(12)
Data Science in Real Life from Johns Hopkins University ★★★☆☆(12)
Data Science Math Skills from Duke University ★★★★☆(12)
Data Structures & Algorithms I: ArrayLists, LinkedLists, Stacks and Queues from Georgia Institute of Technology ★★★★★(12)
Discrete Optimization from University of Melbourne ★★★★☆(12)
Introduction to Software Product Management from University of Alberta ★★★★☆(12)
Data Science: R Basics from Harvard University ★★★★★(11)
Interactivity with JavaScript from University of Michigan ★★★★☆(11)
Human-Computer Interaction I: Fundamentals & Design Principles from Georgia Institute of Technology ★★★★★(11)
Biology Meets Programming: Bioinformatics for Beginners from University of California, San Diego ★★★☆☆(10)
Programming Languages from University of Virginia ★★★☆☆(10)
Learning from Data (Introductory Machine Learning course) from California Institute of Technology ★★★★★(10)
Full Stack Foundations
Managing Data Analysis from Johns Hopkins University ★★★☆☆(9)
Data Visualization and Communication with Tableau from Duke University ★★★★☆(9)
Cloud Computing Applications, Part 1: Cloud Systems and Infrastructure from University of Illinois at Urbana-Champaign ★★★☆☆(9)
Algorithmic Thinking (Part 2) from Rice University ★★★★☆(9)
Data Wrangling with MongoDB from MongoDB University ★★★☆☆(9)
Advanced Styling with Responsive Design from University of Michigan ★★★★☆(8)
Machine Learning Fundamentals from University of California, San Diego ★★★★☆(8)
Foundations of Data Analysis - Part 1: Statistics Using R from The University of Texas at Austin ★★★★☆(8)
Cryptography from University of Maryland, College Park ★★★★☆(8)
MATLAB and Octave for Beginners from École Polytechnique Fédérale de Lausanne ★★★★☆(8)
Image and Video Processing: From Mars to Hollywood with a Stop at the Hospital from Duke University ★★★★☆(7)
Guided Tour of Machine Learning in Finance from New York University (NYU) ★☆☆☆☆(7)
Software Testing from University of Utah ★★★★☆(7)
Intro to DevOps from Nutanix ★★★☆☆(7)
Computer Graphics from University of California, San Diego ★★★★☆(6)
Data Structures and Performance from University of California, San Diego ★★★★☆(6)
Internet of Things: How did we get here? from University of California, San Diego ★★☆☆☆(6)
Computer Architecture from Princeton University ★★★★☆(6)
Analysis of Algorithms from Princeton University ★★★★☆(6)
Managing Big Data with MySQL from Duke University ★★★★☆(6)
Computer Networking from Georgia Institute of Technology ★★★★☆(6)
Data Structures & Algorithms II: Binary Trees, Heaps, SkipLists and HashMaps from Georgia Institute of Technology ★★★★★(6)
Cloud Computing Concepts: Part 2 from University of Illinois at Urbana-Champaign ★★★★★(6)
Web Application Development with JavaScript and MongoDB from University of London International Programmes ★★★★☆(6)
Introduction to Meteor.js Development from University of London International Programmes ★★★★☆(6)
Client Needs and Software Requirements from University of Alberta ★★★★★(6)
Interactive Computer Graphics from University of Tokyo ★★★☆☆(6)
Fundamentals of Machine Learning from Santa Fe Institute ★★★★★(6)
Software Debugging from Saarland University ★★★★★(6)
Intro to Algorithms
Intro to AJAX
Intro to Data Analysis
Networking for Web Developers
Software Construction in Java from Massachusetts Institute of Technology ★★★★★(5)
Internet of Things: Setting Up Your DragonBoard™ Development Platform from University of California, San Diego ★★★☆☆(5)
Data Structures: An Active Learning Approach from University of California, San Diego ★★★★★(5)
Software Development Process from Georgia Institute of Technology ★★★★☆(5)
Cloud Networking from University of Illinois at Urbana-Champaign ★★★★☆(5)
Social Network Analysis from University of California, Davis ★★★★★(5)
Database Management Essentials from University of Colorado System ★★★★☆(5)
Data Management and Visualization from Wesleyan University ★★☆☆☆(5)
JavaScript Promises from Google ★★★★★(5)
Data Science Essentials from Microsoft ★★★★☆(5)
Programming for Everyone – An Introduction to Visual Programming Languages from Weizmann Institute of Science ★★★★☆(5)
Parallel Programming Concepts
Data Visualization and D3.js
Algorithms on Strings from University of California, San Diego ★★★☆☆(4)
The R Programming Environment from Johns Hopkins University ★★★☆☆(4)
Data Manipulation at Scale: Systems and Algorithms from University of Washington ★★★☆☆(4)
Programming Languages, Part B from University of Washington ★★★★☆(4)
Data Analysis Tools from Wesleyan University ★★★☆☆(4)
Querying Data with Transact-SQL from Microsoft ★★★★☆(4)
Programming with Python for Data Science from Microsoft ★★★★☆(4)
Practical Numerical Methods with Python from George Washington University ★★★★☆(4)
Algorithms on Graphs from University of California, San Diego ★★★★☆(3)
Internet of Things: Communication Technologies from University of California, San Diego ★★★☆☆(3)
Mastering the Software Engineering Interview from University of California, San Diego ★★★★☆(3)
Big Data Modeling and Management Systems from University of California, San Diego ★★★☆☆(3)
Big Data Integration and Processing from University of California, San Diego ★★★★☆(3)
Algorithmic Design and Techniques from University of California, San Diego ★★★★☆(3)
Machine Learning: Unsupervised Learning from Brown University ★★★☆☆(3)
Software Architecture & Design from Georgia Institute of Technology ★★★★★(3)
Human-Computer Interaction II: Cognition, Context & Culture from Georgia Institute of Technology ★★★★★(3)
Data Structures & Algorithms III: AVL and 2-4 Trees, Divide and Conquer Algorithms from Georgia Institute of Technology ★★★★★(3)
Framework for Data Collection and Analysis from University of Maryland, College Park ★★★★☆(3)
Data Warehouse Concepts, Design, and Data Integration from University of Colorado System ★★★☆☆(3)
Service-Oriented Architecture from University of Alberta ★★★★☆(3)
Website Performance Optimization from Google ★★★★☆(3)
DevOps for Developers: How to Get Started from Microsoft ★★★★☆(3)
Build a Modern Computer from First Principles: Nand to Tetris Part II (project-centered course) from Hebrew University of Jerusalem ★★★★★(3)
Data Mining with Weka from University of Waikato ★★★★☆(3)
MongoDB for .NET Developers
Configuring Linux Web Servers
Language, Proof and Logic from Stanford University ★★★★★(2)
Mobile Application Experiences Part 1: From a Domain to an App Idea from Massachusetts Institute of Technology ★★★★★(2)
Software Development Fundamentals from University of Pennsylvania ★★★☆☆(2)
Building R Packages from Johns Hopkins University ★★★☆☆(2)
Data Science: Computational Thinking with Python from University of California, Berkeley ★★★★★(2)
Advanced Data Structures in Java from University of California, San Diego ★★★★☆(2)
Introduction to Machine Learning from Duke University ★★★★☆(2)
Human-Computer Interaction IV: Evaluation, Agile Methods & Beyond from Georgia Institute of Technology ★★★★★(2)
Programming Languages, Part C from University of Washington ★★★★☆(2)
Data Analytics Foundations for Accountancy I from University of Illinois at Urbana-Champaign ★☆☆☆☆(2)
Object-Oriented Data Structures in C++ from University of Illinois at Urbana-Champaign ★★★★☆(2)
Responsive Website Tutorial and Examples from University of London International Programmes ★★★★★(2)
How to Code: Complex Data from The University of British Columbia ★★★★★(2)
Fundamentals of Visualization with Tableau from University of California, Davis ★★★★☆(2)
Algorithms from Indian Institute of Technology Bombay ★★★★★(2)
Software Testing Management from University System of Maryland ★★☆☆☆(2)
Web Application Development: Basic Concepts from University of New Mexico ★★★★★(2)
Client-Server Communication from Google ★★★★★(2)
Introduction to Computation Theory from Santa Fe Institute ★★★★★(2)
Developing International Software, Part 1 from Microsoft ★★★★☆(2)
Principles of Machine Learning from Microsoft ★★★★★(2)
Data, Analytics, and Learning from University of Texas Arlington ★★☆☆☆(2)
Fundamentals of Machine Learning in Finance from New York University (NYU) ★★☆☆☆(2)
Autonomous Mobile Robots from ETH Zurich ★★★★★(2)
Knowledge Management and Big Data in Business from Hong Kong Polytechnic University ★★★★☆(2)
Approximation Algorithms Part I from École normale supérieure ★★★★★(2)
Introduction to Process Mining with ProM from Eindhoven University of Technology ★★★★☆(2)
HTML5 Apps and Games from World Wide Web Consortium (W3C) ★★☆☆☆(2)
Intro to Theoretical Computer Science
Compilers from Stanford University ★★★★★(1)
Graph Search, Shortest Paths, and Data Structures from Stanford University ★☆☆☆☆(1)
Computation Structures 2: Computer Architecture from Massachusetts Institute of Technology ★★★★☆(1)
Computational Thinking for Modeling and Simulation from Massachusetts Institute of Technology ★★☆☆☆(1)
Advanced Algorithms and Complexity from University of California, San Diego ★★★☆☆(1)
Advanced R Programming from Johns Hopkins University ★★★★☆(1)
Advanced Linear Models for Data Science 2: Statistical Linear Models from Johns Hopkins University ★★★★★(1)
Foundations of Healthcare Systems Engineering from Johns Hopkins University ★★★★★(1)
Programming for the Internet of Things Project from University of California, Irvine ★★★★☆(1)
Intro to Analytic Thinking, Data Science, and Data Mining from University of California, Irvine ★★★★★(1)
Basic Data Processing and Visualization from University of California, San Diego ★★★☆☆(1)
Database Systems Concepts & Design from Georgia Institute of Technology ★★★★☆(1)
Human-Computer Interaction III: Ethics, Needfinding & Prototyping from Georgia Institute of Technology ★★★★★(1)
Data Structures & Algorithms IV: Pattern Matching, Dijkstra’s, MST, and Dynamic Programming Algorithms from Georgia Institute of Technology ★★★★★(1)
Blockchain Basics from University at Buffalo ★★☆☆☆(1)
Mathematics for Computer Science from University of London International Programmes ★★★★★(1)
Software Construction: Data Abstraction from The University of British Columbia ★★★☆☆(1)
Software Construction: Object-Oriented Design from The University of British Columbia ★★☆☆☆(1)
DevOps Culture and Mindset from University of California, Davis ★★★★★(1)
Software Development Processes and Methodologies from University of Minnesota ★★★☆☆(1)
Server-side Development with NodeJS, Express and MongoDB from The Hong Kong University of Science and Technology ★★★★★(1)
Essential Linear Algebra for Data Science from University of Colorado Boulder ★★★★☆(1)
Data Analysis: Visualization and Dashboard Design from Delft University of Technology ★★★☆☆(1)
Automated Software Testing: Unit Testing, Coverage Criteria and Design for Testability from Delft University of Technology ★★★★☆(1)
Automated Software Testing: Model and State-based Testing from Delft University of Technology ★★★★★(1)
Fundamentals of Network Communication from University of Colorado System ★★★★★(1)
Linux Server Management and Security from University of Colorado System ★★★☆☆(1)
Hacking and Patching from University of Colorado System ★★★★★(1)
Formal Software Verification from University System of Maryland ★★☆☆☆(1)
Software Architecture for the Internet of Things from EIT Digital ★★★★☆(1)
Paradigms of Computer Programming from Université catholique de Louvain ★★★★☆(1)
Client-based Web Applications development: ReactJS & Angular from Universidad Politécnica de Madrid ★☆☆☆☆(1)
Advanced Algorithmics and Graph Theory with Python from Institut Mines-Télécom ★★★★★(1)
Browser Rendering Optimization from Google ★★★★☆(1)
Google Maps APIs from Google ★★★★★(1)
Cybersecurity and Mobility from University System of Georgia ★☆☆☆☆(1)
Developing SQL Databases from Microsoft ★★☆☆☆(1)
Introduction to TypeScript 2 from Microsoft ★☆☆☆☆(1)
Building Interactive Prototypes using JavaScript from Microsoft ★★★★☆(1)
Introduction to C# from Microsoft ★☆☆☆☆(1)
Algorithms and Data Structures from Microsoft ★★☆☆☆(1)
Algorithms and Data Structures in C# from Microsoft ★★★★★(1)
2D Game Development with libGDX from Amazon ★★★★★(1)
Overview of Advanced Methods of Reinforcement Learning in Finance from New York University (NYU) ★☆☆☆☆(1)
Advanced Database Queries from New York University (NYU) ★★★★★(1)
Advanced Database Administration from New York University (NYU) ★★★★★(1)
Introduction to Cloud Infrastructure Technologies from Linux Foundation ★★★★☆(1)
用Python玩转数据 Data Processing Using Python from Nanjing University ★★★★★(1)
Data Processing Using Python from Nanjing University ★★★☆☆(1)
Fundamentals of Parallelism on Intel Architecture from Intel ★★★★★(1)
An Introduction to Practical Deep Learning from Intel ★★★☆☆(1)
How to Win Coding Competitions: Secrets of Champions from ITMO University ★★★☆☆(1)
Hacker101 from HackerOne ★★★★★(1)
Diseño de Sistemas de información gerencial para Internet con MySQL / PHP y Joomla from Universidad del Rosario ★★★★★(1)
Technical Interview from Pramp ★★★★★(1)
Designing RESTful APIs
MongoDB for Javascript Developers
Quantitative Methods for Biology from Harvard University
Fundamentals of TinyML from Harvard University
Probabilistic Graphical Models 3: Learning from Stanford University
Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming from Stanford University
Shortest Paths Revisited, NP-Complete Problems and What To Do About Them from Stanford University
Algorithms: Design and Analysis, Part 1 from Stanford University
Algorithms: Design and Analysis, Part 2 from Stanford University
Mobile Application Experiences Part 3: Building Mobile Apps from Massachusetts Institute of Technology
Advanced Software Construction in Java from Massachusetts Institute of Technology
Mobile Application Experiences from Massachusetts Institute of Technology
Machine Learning for Healthcare from Massachusetts Institute of Technology
Data Structures and Software Design from University of Pennsylvania
Algorithm Design and Analysis from University of Pennsylvania
Data Analysis Using Python from University of Pennsylvania
Building Web Applications in Django from University of Michigan
Django Features and Libraries from University of Michigan
Web Application Technologies and Django from University of Michigan
Building Web Applications in Django from University of Michigan
Django Features and Libraries from University of Michigan
Developing AR/VR/MR/XR Apps with WebXR, Unity & Unreal from University of Michigan
Intro to AR/VR/MR/XR: Technologies, Applications & Issues from University of Michigan
Introduction to Machine Learning in Sports Analytics from University of Michigan
Database Architecture, Scale, and NoSQL with Elasticsearch from University of Michigan
Introduction to Neurohacking In R from Johns Hopkins University
Building Data Visualization Tools from Johns Hopkins University
Exploratory Data Analysis from Johns Hopkins University
The Merkle Tree and Cryptocurrencies from University of California, Irvine
Data Science: Machine Learning and Predictions from University of California, Berkeley
Blockchain Technology from University of California, Berkeley
Data, Models and Decisions in Business Analytics from Columbia University
Internet of Things: Sensing and Actuation From Devices from University of California, San Diego
Minecraft, Coding and Teaching from University of California, San Diego
How Virtual Reality Works from University of California, San Diego
Introduction to Genomic Data Science from University of California, San Diego
Data Structures Fundamentals from University of California, San Diego
Graph Algorithms from University of California, San Diego
String Processing and Pattern Matching Algorithms from University of California, San Diego
Computer Science: Algorithms, Theory, and Machines from Princeton University
Java Programming: Build a Recommendation System from Duke University
Cloud Data Engineering from Duke University
Cloud Virtualization, Containers and APIs from Duke University
Machine Learning Foundations for Product Managers from Duke University
Managing Machine Learning Projects from Duke University
Web Applications and Command-Line Tools for Data Engineering from Duke University
Human-Computer Interaction from Georgia Institute of Technology
Software Analysis & Testing from Georgia Institute of Technology
Introduction to Graduate Algorithms from Georgia Institute of Technology
Network Function Virtualization from Georgia Institute of Technology
Cloud Systems Software from Georgia Institute of Technology
Cloud Applications from Georgia Institute of Technology
Cybersecurity: The CISO's View from University of Washington
Building a Cybersecurity Toolkit from University of Washington
Finding Your Cybersecurity Career Path from University of Washington
Machine Teaching for Autonomous AI from University of Washington
Designing Autonomous AI from University of Washington
Building Autonomous AI from University of Washington
Data Analytics Foundations for Accountancy II from University of Illinois at Urbana-Champaign
Data Modeling and Regression Analysis in Business from University of Illinois at Urbana-Champaign
Unordered Data Structures from University of Illinois at Urbana-Champaign
Ordered Data Structures from University of Illinois at Urbana-Champaign
Machine Learning for Accounting with Python from University of Illinois at Urbana-Champaign
Machine Learning Algorithms with R in Business Analytics from University of Illinois at Urbana-Champaign
Advanced Deep Learning Methods for Healthcare from University of Illinois at Urbana-Champaign
Blockchain Platforms from University at Buffalo
Smart Contracts from University at Buffalo
Decentralized Applications (Dapps) from University at Buffalo
Data Analysis and Visualization from University at Buffalo
Supercomputing from Partnership for Advanced Computing in Europe
Introduction to Predictive Analytics using Python from University of Edinburgh
Foundations of Data Science: K-Means Clustering in Python from University of London International Programmes
Introduction to Applied Cryptography from University of London International Programmes
Implementation Strategies: AI and Cognitive Computing from The University of British Columbia
Implementation Strategies: Cloud Computing from The University of British Columbia
Worldbuilding for Video Games from The University of British Columbia
Creating Dashboards and Storytelling with Tableau from University of California, Davis
Essential Design Principles for Tableau from University of California, Davis
Continuous Integration from University of California, Davis
Data Wrangling, Analysis and AB Testing with SQL from University of California, Davis
Identifying Security Vulnerabilities in C/C++Programming from University of California, Davis
Exploiting and Securing Vulnerabilities in Java Applications from University of California, Davis
Distributed Computing with Spark SQL from University of California, Davis
Game Design and Development 3: 3D Shooter from Michigan State University
Game Design and Development 2: 2D Platformer from Michigan State University
Game Design and Development 1: 2D Shooter from Michigan State University
Game Design and Development 4: 3D Platformer from Michigan State University
Moving to the Cloud from University of Melbourne
Signals, Systems, and Learning from Rice University
Bioinformatics: Introduction and Methods 生物信息学: 导论与方法 from Peking University
面向对象技术高级课程（The Advanced Object-Oriented Technology） from Peking University
操作系统与虚拟化安全 from Peking University
计算机组成 Computer Organization from Peking University
计算机辅助翻译原理与实践 Principles and Practice of Computer-Aided Translation from Peking University
数据结构基础 from Peking University
高级数据结构与算法 from Peking University
操作系统原理（Operating Systems） from Peking University
算法设计与分析 Design and Analysis of Algorithms from Peking University
算法基础 from Peking University
算法设计与分析(高级) | Advanced Design and Analysis of Algorithms from Peking University
Java程序设计 from Peking University
LAFF – On Programming for Correctness from The University of Texas at Austin
Lean Software Development from University of Minnesota
Engineering Practices for Building Quality Software from University of Minnesota
Introduction to Automated Analysis from University of Minnesota
Web and Mobile Testing with Selenium from University of Minnesota
Black-box and White-box Testing from University of Minnesota
Front-End Web UI Frameworks and Tools: Bootstrap 4 from The Hong Kong University of Science and Technology
Mathematical Methods for Data Analysis from The Hong Kong University of Science and Technology
Software Engineering: Modeling Software Systems using UML from The Hong Kong University of Science and Technology
Software Engineering: Implementation and Testing from The Hong Kong University of Science and Technology
Software Engineering: Software Design and Project Management from The Hong Kong University of Science and Technology
Big Data for Reliability and Security from Purdue University
Introduction to Deep Learning from Purdue University
Dealing With Missing Data from University of Maryland, College Park
Project Planning and Machine Learning from University of Colorado Boulder
Algorithms for Searching, Sorting, and Indexing from University of Colorado Boulder
Dynamic Programming, Greedy Algorithms from University of Colorado Boulder
Data Mining Methods from University of Colorado Boulder
Fundamentals of Software Architecture for Big Data from University of Colorado Boulder
Advanced Topics and Future Trends in Database Technologies from University of Colorado Boulder
Applications of Software Architecture for Big Data from University of Colorado Boulder
Software Architecture Patterns for Big Data from University of Colorado Boulder
Data Analysis: Building Your Own Business Dashboard from Delft University of Technology
Global Software Development from Delft University of Technology
Fundamentals of Quantum Information from Delft University of Technology
Homeland Security & Cybersecurity Connection - It's Not About the Terrorists from University of Colorado System
Peer-to-Peer Protocols and Local Area Networks from University of Colorado System
Packet Switching Networks and Algorithms from University of Colorado System
Detecting and Mitigating Cyber Threats and Attacks from University of Colorado System
Design and Analyze Secure Networked Systems from University of Colorado System
Basic Cryptography and Programming with Crypto API from University of Colorado System
Asymmetric Cryptography and Key Management from University of Colorado System
Symmetric Cryptography from University of Colorado System
Software Design Threats and Mitigations from University of Colorado System
Requirements Specifications: Goals and Conflict Analysis from University of Colorado System
SRS Documents: Requirements and Diagrammatic Notations from University of Colorado System
Requirements Gathering for Secure Software Development from University of Colorado System
Software Requirements Prioritization: Risk Analysis from University of Colorado System
Requirements Elicitation: Artifact and Stakeholder Analysis from University of Colorado System
Data Structures and Design Patterns for Game Developers from University of Colorado System
Cloud Computing Security from University of Colorado System
Advanced System Security Topics from University of Colorado System
Algorithms, Data Collection, and Starting to Code from University of Colorado System
Data Analysis and Representation, Selection and Iteration from University of Colorado System
Implementation of Data Structures from Indian Institute of Technology Bombay
Foundations of Data Structures from Indian Institute of Technology Bombay
I sistemi Operativi Moderni from University of Naples Federico II
Nuove tecnologie digitali from University of Naples Federico II
Laboratorio di programmazione: strumenti e programmi from University of Naples Federico II
NoSQL systems from Universidad Nacional Autónoma de México
Designing data-intensive applications from Universidad Nacional Autónoma de México
Relational database systems from Universidad Nacional Autónoma de México
Cognición encarnada from Universidad Nacional Autónoma de México
Software Testing Fundamentals from University System of Maryland
Data Structures and Algorithm Design Part I | 数据结构与算法设计(上) from Tsinghua University
Data Structures and Algorithms (I) from Tsinghua University
Data Structures and Algorithms (II) from Tsinghua University
Data Structures and Algorithms (III) from Tsinghua University
Data Structures and Algorithms (IV) from Tsinghua University
Algoritmos y Programación en R from Tecnológico de Monterrey
Enterprise Software Lifecycle Management from National Research Nuclear University MEPhI
Data Processing and Analysis with Excel from Rochester Institute of Technology
Data Representation and Visualization in Tableau from Rochester Institute of Technology
Getting Started with Unreal Engine from Rochester Institute of Technology
Artificial Intelligence: An Overview from Politecnico di Milano
Machine Learning: an overview from Politecnico di Milano
The Software Architect Code: Building the Digital World from Universidad Carlos iii de Madrid
Introduction to Java Programming: Fundamental Data Structures and Algorithms from Universidad Carlos iii de Madrid
Introduction to Architecting Smart IoT Devices from EIT Digital
Architecting Smart IoT Devices from EIT Digital
I/O-efficient algorithms from EIT Digital
Reviews & Metrics for Software Improvements from University of Alberta
Cybersecurity and Privacy in the IoT from Curtin University
Communicating with Robots and Bots from Curtin University
Understanding Artificial Intelligence through Algorithmic Information Theory from Institut Mines-Télécom
Procedural Modelling from National University of Singapore
Using Machine Learning in Trading and Finance from New York Institute of Finance
Introdução ao Teste de Software from Universidade de São Paulo
Intro to Data Structures and Algorithms from Google
Offline Web Applications from Google
Intro to Progressive Web Apps from Google
Introduction to Data Structures from University of Adelaide
Programming for Data Science from University of Adelaide
Cybersecurity and the X-Factor from University System of Georgia
Cybersecurity and the Internet of Things from University System of Georgia
Programming in R for Data Science from Microsoft
Developing Intelligent Apps and Bots from Microsoft
Applied Machine Learning from Microsoft
AngularJS: Framework Fundamentals from Microsoft
Implementing In-Memory SQL Database Objects from Microsoft
Building Functional Prototypes using Node.js from Microsoft
Application Design Considerations: An Inclusive Approach from Microsoft
Designing Data Platform Solutions from Microsoft
Network Security & Database Vulnerabilities from IBM
Cybersecurity Compliance Framework & System Administration from IBM
Real-Time Cyber Threat Detection and Mitigation from New York University (NYU)
Enterprise and Infrastructure Security from New York University (NYU)
Information Security - Introduction to Information Security from New York University (NYU)
Information Security - Advanced topics from New York University (NYU)
Penetration Testing - Discovering Vulnerabilities from New York University (NYU)
Penetration Testing - Post Exploitation from New York University (NYU)
Quantum Computer Systems Design I: Intro to Quantum Computation and Programming from The University of Chicago
Quantum Computer Systems Design II: Principles of Quantum Architecture from The University of Chicago
Quantum Computer Systems Design III: Working with Noisy Systems from The University of Chicago
Blockchain Scalability and its Foundations in Distributed Systems from The University of Sydney
Introduction to DevOps: Transforming and Improving Operations from Linux Foundation
Introduction to Kubernetes from Linux Foundation
Business Considerations for 5G with Edge, IoT, and AI from Linux Foundation
Open Source and the 5G Transition from Linux Foundation
Introduction to Serverless on Kubernetes from Linux Foundation
Web App Development with the Power of Node.js from Technische Universität München (Technical University of Munich)
IoT System Architecture: Design and Evaluation from Waseda University
UML Class Diagrams for Software Engineering from KU Leuven University
Data Science in the Games Industry from University of Dundee
Internet of Things for Active Ageing from Taipei Medical University
Orientação a Objetos com Java from Instituto Tecnológico de Aeronáutica
Computer Architecture from Harvey Mudd College
More Data Mining with Weka from University of Waikato
Introduction: Elements of Microgame Design from Worcester Polytechnic Institute
Using R for Regression and Machine Learning in Investment from Sungkyunkwan University
Mejora tu Negocio con Inteligencia Artificial from Universidad Anáhuac
Defensive Programming and Debugging from Partnership for Advanced Computing in Europe
Python in High Performance Computing from Partnership for Advanced Computing in Europe
Concurrency from AdaCore University
Introduction to Applied Machine Learning from Alberta Machine Intelligence Institute
Bias and Discrimination in AI from Université de Montréal
Deep Learning Essentials from Université de Montréal
Code of Life – When Computer Science Meets Genetics
Dynamic Web Applications with Sinatra
Deploying Applications with Heroku
VR Scenes and Objects
MongoDB for Python Developers

Advanced (187)

The Analytics Edge from Massachusetts Institute of Technology ★★★★★(80)
Machine Learning Foundations: A Case Study Approach from University of Washington ★★★★☆(40)
Sample-based Learning Methods from University of Alberta ★★★★★(40)
Computer Simulations from University of California, Davis ★★★★★(38)
Introducción al diseño de hardware con Verilog from Galileo University ★★★★★(38)
Introduction to Artificial Intelligence from Stanford University ★★★★☆(27)
[New] Machine Learning for Computer Vision from MathWorks
Fundamentals of Reinforcement Learning from University of Alberta ★★★★★(24)
Pattern Discovery in Data Mining from University of Illinois at Urbana-Champaign ★★☆☆☆(21)
Machine Learning: Regression from University of Washington ★★★★★(20)
Statistical Thinking for Data Science and Analytics from Columbia University ★★☆☆☆(19)
Bitcoin and Cryptocurrency Technologies from Princeton University ★★★★☆(19)
Prediction and Control with Function Approximation from University of Alberta ★★★★★(19)
Probabilistic Graphical Models 1: Representation from Stanford University ★★★★☆(18)
Developing Data Products from Johns Hopkins University ★★★★☆(18)
Finding Hidden Messages in DNA (Bioinformatics I) from University of California, San Diego ★★★★★(17)
Neural Networks and Deep Learning from DeepLearning.AI ★★★★★(15)
Machine Learning for Data Science and Analytics from Columbia University ★★★☆☆(15)
Machine Learning With Big Data from University of California, San Diego ★★☆☆☆(14)
Artificial Intelligence (AI) from Columbia University ★★★★☆(12)
Machine Learning from Columbia University ★★★★☆(12)
Text Mining and Analytics from University of Illinois at Urbana-Champaign ★★★★☆(10)
Hardware Security from University of Maryland, College Park ★★★☆☆(10)
Applied Plotting, Charting & Data Representation in Python from University of Michigan ★★☆☆☆(9)
Machine Learning: Classification from University of Washington ★★★★★(9)
Mathematics for Machine Learning: Multivariate Calculus from Imperial College London ★★★★★(9)
Convolutional Neural Networks from DeepLearning.AI ★★★★★(8)
Reinforcement Learning from Brown University ★★★☆☆(8)
Practical Deep Learning For Coders from fast.ai ★★★★☆(8)
Cluster Analysis in Data Mining from University of Illinois at Urbana-Champaign ★★★☆☆(7)
Structuring Machine Learning Projects from DeepLearning.AI ★★★★☆(6)
Applied Machine Learning in Python from University of Michigan ★★★★☆(6)
Enabling Technologies for Data Science and Analytics: The Internet of Things from Columbia University ★☆☆☆☆(6)
Graph Analytics for Big Data from University of California, San Diego ★★★☆☆(6)
Machine Learning from Georgia Institute of Technology ★★★★☆(6)
Advanced Operating Systems from Georgia Institute of Technology ★★★★★(6)
Interactive 3D Graphics from Autodesk ★★★★☆(6)
Model Building and Validation from AT&T ★★☆☆☆(6)
Machine Learning: Clustering & Retrieval from University of Washington ★★★★★(5)
Applied Cryptography from University of Virginia ★★★★☆(5)
Introduction to Computer Architecture from Carnegie Mellon University ★★★★★(5)
Sparse Representations in Image Processing: From Theory to Practice from Technion - Israel Institute of Technology ★★★★★(5)
Genome Sequencing (Bioinformatics II) from University of California, San Diego ★★★★★(4)
Machine Learning for Data Analysis from Wesleyan University ★★★★☆(4)
Probabilistic Graphical Models 2: Inference from Stanford University ★★★★☆(3)
Applied Social Network Analysis in Python from University of Michigan ★★★★☆(3)
Practical Predictive Analytics: Models and Methods from University of Washington ★★☆☆☆(3)
Regression Modeling in Practice from Wesleyan University ★★★★☆(3)
Mathematics for Machine Learning: PCA from Imperial College London ★★☆☆☆(3)
Quantitative Formal Modeling and Worst-Case Performance Analysis from EIT Digital ★★★☆☆(3)
Comparing Genes, Proteins, and Genomes (Bioinformatics III) from University of California, San Diego ★★★★★(2)
Genomic Data Science and Clustering (Bioinformatics V) from University of California, San Diego ★★★★☆(2)
Knowledge-Based AI: Cognitive Systems from Georgia Institute of Technology ★★★☆☆(2)
Introduction to Operating Systems from Georgia Institute of Technology ★★★★★(2)
Intro to Information Security from Georgia Institute of Technology ★★☆☆☆(2)
Cloud Computing Applications, Part 2: Big Data and Applications in the Cloud from University of Illinois at Urbana-Champaign ★★★☆☆(2)
Foundations of Data Analysis - Part 2: Inferential Statistics from The University of Texas at Austin ★★★★☆(2)
Introduction to Deep Learning from Higher School of Economics ★★★☆☆(2)
Nearest Neighbor Collaborative Filtering from University of Minnesota ★★☆☆☆(2)
Data Mining: Theories and Algorithms for Tackling Big Data | 数据挖掘：理论与算法 from Tsinghua University ★★★☆☆(2)
Reinforcement Learning in Finance from New York University (NYU) ★☆☆☆☆(2)
Real-Time Analytics with Apache Storm from Twitter ★★★★☆(2)
Advanced Linear Models for Data Science 1: Least Squares from Johns Hopkins University ★★★★★(1)
Artificial Intelligence for Breast Cancer Detection from Johns Hopkins University ★★★★☆(1)
High Performance Computer Architecture from Georgia Institute of Technology ★★★★★(1)
Computational Photography from Georgia Institute of Technology ★★★★☆(1)
Computability, Complexity & Algorithms from Georgia Institute of Technology ★★★★★(1)
Network Security from Georgia Institute of Technology ★★★★★(1)
Big Data, Genes, and Medicine from State University of New York ★★★★☆(1)
Quantum Machine Learning from University of Toronto ★★★★★(1)
Parallel Programming in Java from Rice University ★★★★☆(1)
Concurrent Programming in Java from Rice University ★★★★★(1)
Relational Database Support for Data Warehouses from University of Colorado System ★★☆☆☆(1)
Big Data Analysis with Scala and Spark from École Polytechnique Fédérale de Lausanne ★★★☆☆(1)
Nature, in Code: Biology in JavaScript from École Polytechnique Fédérale de Lausanne ★★★☆☆(1)
Hands-on Text Mining and Analytics from Yonsei University ★★★★★(1)
Optimize ML Models and Deploy Human-in-the-Loop Pipelines from DeepLearning.AI ★★★★☆(1)
DevOps Practices and Principles from Microsoft ★★☆☆☆(1)
Deep Learning and Reinforcement Learning from IBM ★★★☆☆(1)
Introduction to Cloud Foundry and Cloud Native Software Architecture from Linux Foundation ★★★★★(1)
Sparse Representations in Signal and Image Processing: Fundamentals from Technion - Israel Institute of Technology ★★★★★(1)
AI for Medical Diagnosis from DeepLearning.AI ★★★★☆(1)
Big Data Science with the BD2K-LINCS Data Coordination and Integration Center from Icahn School of Medicine at Mount Sinai ★★★★☆(1)
Security Operations and Administration from (ISC)² ★★★★★(1)
Systems and Application Security from (ISC)² ★★★★☆(1)
Identifying, Monitoring, and Analyzing Risk and Incident Response and Recovery from (ISC)² ★★★★☆(1)
Principles, Statistical and Computational Tools for Reproducible Data Science from Harvard University
Unsupervised Learning, Recommenders, Reinforcement Learning from DeepLearning.AI
Advanced Learning Algorithms from DeepLearning.AI
Real-Time Audio Signal Processing in Faust from Stanford University
Computation Structures 3: Computer Organization from Massachusetts Institute of Technology
Number Theory and Cryptography from University of California, San Diego
Introduction to Concurrent Programming with GPUs from Johns Hopkins University
Cryptography and Hashing Overview from University of California, Irvine
Predictive Modeling, Model Fitting, and Regression Analysis from University of California, Irvine
Cluster Analysis, Association Mining, and Model Evaluation from University of California, Irvine
Data Science: Inferential Thinking through Simulations from University of California, Berkeley
Molecular Evolution (Bioinformatics IV) from University of California, San Diego
Finding Mutations in DNA and Proteins (Bioinformatics VI) from University of California, San Diego
Dynamic Programming: Applications In Machine Learning and Genomics from University of California, San Diego
NP-Complete Problems from University of California, San Diego
Design Thinking and Predictive Analytics for Data Products from University of California, San Diego
Deploying Machine Learning Models from University of California, San Diego
Meaningful Predictive Modeling from University of California, San Diego
High Performance Computing from Georgia Institute of Technology
GT - Refresher - Advanced OS from Georgia Institute of Technology
Artificial Intelligence from Georgia Institute of Technology
Cyber-Physical Systems Security from Georgia Institute of Technology
Compilers: Theory and Practice from Georgia Institute of Technology
FA17: Machine Learning from Georgia Institute of Technology
Machine Learning from Georgia Institute of Technology
Cyber-Physical Systems Design & Analysis from Georgia Institute of Technology
Predictive Analytics using Machine Learning from University of Edinburgh
Plant Bioinformatics from University of Toronto
Advanced Modeling for Discrete Optimization from University of Melbourne
Basic Modeling for Discrete Optimization from University of Melbourne
离散优化建模基础篇 Basic Modeling for Discrete Optimization from The Chinese University of Hong Kong
离散优化建模高阶篇 Advanced Modeling for Discrete Optimization from The Chinese University of Hong Kong
离散优化算法篇 Solving Algorithms for Discrete Optimization from The Chinese University of Hong Kong
Solving Algorithms for Discrete Optimization from University of Melbourne
Basic Data Descriptors, Statistical Distributions, and Application to Business Decisions from Rice University
Quantum Cryptography from California Institute of Technology
LAFF-On Programming for High Performance from The University of Texas at Austin
Machine Learning from The University of Texas at Austin
Обработка изображений from Higher School of Economics
Introduction to Recommender Systems: Non-Personalized and Content-Based from University of Minnesota
Recommender Systems: Evaluation and Metrics from University of Minnesota
Matrix Factorization and Advanced Techniques from University of Minnesota
Computer Applications of Artificial Intelligence and e-Construction from Purdue University
Combining and Analyzing Complex Data from University of Maryland, College Park
Introduction to High-Performance and Parallel Computing from University of Colorado Boulder
Statistical Inference for Estimation in Data Science from University of Colorado Boulder
Classical Cryptosystems and Core Concepts from University of Colorado System
Mathematical Foundations for Cryptography from University of Colorado System
Cryptographic Hash and Integrity Protection from University of Colorado System
Cryptography and Information Theory from University of Colorado System
MATLAB et Octave pour débutants from École Polytechnique Fédérale de Lausanne
Optimization: principles and algorithms - Linear optimization from École Polytechnique Fédérale de Lausanne
Optimization: principles and algorithms - Network and discrete optimization from École Polytechnique Fédérale de Lausanne
Optimization: principles and algorithms - Unconstrained nonlinear optimization from École Polytechnique Fédérale de Lausanne
Il linguaggio naturale, dall'uomo alla macchina from University of Naples Federico II
Machine Learning e Data Mining in R from University of Naples Federico II
機器學習基石下 (Machine Learning Foundations)---Algorithmic Foundations from National Taiwan University
人工智慧：搜尋方法與邏輯推論 (Artificial Intelligence - Search & Logic) from National Taiwan University
人工智慧：機器學習與理論基礎 (Artificial Intelligence - Learning & Theory) from National Taiwan University
Operations Research (1): Models and Applications from National Taiwan University
Operations Research (2): Optimization Algorithms from National Taiwan University
Sesenta años de inteligencia artificial from Universidad Nacional Autónoma de México
Razonamiento artificial from Universidad Nacional Autónoma de México
DNA Sequences: Alignments and Analysis from University System of Maryland
计算几何 | Computational Geometry from Tsinghua University
Big Data Machine Learning | 大数据机器学习 from Tsinghua University
System Validation: Automata and behavioural equivalences from EIT Digital
System Validation (2): Model process behaviour from EIT Digital
System Validation (4): Modelling Software, Protocols, and other behaviour from EIT Digital
System Validation (3): Requirements by modal formulas from EIT Digital
Approximation Algorithms from EIT Digital
Automated Reasoning: Symbolic Model Checking from EIT Digital
Generative Modelling from National University of Singapore
Performative Modelling from National University of Singapore
Infrastructure as Code from Microsoft
DevOps Testing from Microsoft
DevOps for Databases from Microsoft
Secure Software Development: Verification and More Specialized Topics from Linux Foundation
Secure Software Development: Requirements, Design, and Reuse from Linux Foundation
Introduction to RISC-V from Linux Foundation
Building a RISC-V CPU Core from Linux Foundation
RISC-V Toolchain and Compiler Optimization Techniques from Linux Foundation
Cyber-Physical Systems: Modeling and Simulation from University of California, Santa Cruz
Introduction to Statistical Methods for Gene Mapping from Kyoto University
AI for Medical Prognosis from DeepLearning.AI
AI For Medical Treatment from DeepLearning.AI
Build Basic Generative Adversarial Networks (GANs) from DeepLearning.AI
Build Better Generative Adversarial Networks (GANs) from DeepLearning.AI
Apply Generative Adversarial Networks (GANs) from DeepLearning.AI
Generative Deep Learning with TensorFlow from DeepLearning.AI
Custom Models, Layers, and Loss Functions with TensorFlow from DeepLearning.AI
Deploying Machine Learning Models in Production from DeepLearning.AI
Machine Learning Modeling Pipelines in Production from DeepLearning.AI
Machine Learning Data Lifecycle in Production from DeepLearning.AI
Introduction to Machine Learning in Production from DeepLearning.AI
Computer System Design: Advanced Concepts of Modern Microprocessors from Chalmers University of Technology
Approximation Algorithms Part II from École normale supérieure
Reliable Distributed Algorithms - Part 2 from KTH Royal Institute of Technology
Access Controls from (ISC)²
Networks and Communications Security from (ISC)²
Optimizing Machine Learning Performance from Alberta Machine Intelligence Institute

Learn Bootstrap 5 in Spanish by Building a Portfolio Website – Bootstrap Course for Beginners

Estefania Cassingena Navone — Thu, 10 Nov 2022 05:30:10 +0000

Welcome! If you speak Spanish and you want to practice your HTML and CSS skills, create responsive websites with Bootstrap 5, and build your portfolio website, then this course is for you.

In this article, you will find a brief introduction to responsive web development and Bootstrap 5. You will also learn why you should learn them if your goal is to be a front-end web developer.

Then, you will find a 5-hour Bootstrap 5 course on the freeCodeCamp Spanish YouTube channel. In this course, you can learn the fundamentals in Spanish and build your portfolio website step by step using Bootstrap components, icons, and grid.

If you have Spanish-speaking friends, you are welcome to share the Spanish version of this article with them.

💡 Tip: to take the course, you should have previous knowledge of HTML and CSS. If you need to review these topics, I invite you to take our full courses on the Spanish YouTube channel.

Let's begin! ✨

🔹 What is Bootstrap?

Let's start with an introduction to Bootstrap. The official Bootstrap documentation defines it as a:

Powerful, extensible, and feature-packed frontend toolkit.

Bootstrap 5 - Official Website

Let's see the main keywords of this definition more closely:

Bootstrap is powerful because it has many features, including pre-defined CSS classes that you can apply to your HTML elements to assign style instantly. With Bootstrap, you can also use powerful JavaScript plugins to create elements like carousels, modals, tooltips, and more.
Bootstrap is extensible because you can extend or customize the pre-defined CSS classes that come with Bootstrap to fit your needs. If you ever need to change a color, you can do so with custom CSS selectors, ids, and classes. You can also customize the JavaScript code that powers certain Bootstrap components.
Bootstrap is used for front-end web development because this area of web development focuses on designing and developing the user interface, the part of the website that users see and interact with directly.

💡 Tip: basically, Bootstrap gives you all the tools you need to develop responsive websites with pre-defined components, icons, and styles.

Examples of Bootstrap Components (source)

🔶 Importance of Creating a Developer Portfolio

Developing your portfolio website is very important to showcase your knowledge, skills, and the projects you have worked on during your learning journey.

Think about it...

What is the best way to prove your knowledge and skills?

The answer is: creating real-world projects.

That is exactly what employers are looking for – developers who can learn new technologies and apply them to new scenarios.

Creating a project is a great way to show that you have the right skills and the motivation to work as a web developer.

Great. Now you know why it is important to create your developer portfolio, so let's see the portfolio website that you will create. 🔅

🔸 Course Project

This is the main structure of the portfolio website project that we will build during the course:

Hero Section and About Me Section

This section will have a navigation bar and a profile image. The navigation bar will be responsive. A burger icon will be displayed in small devices (instead of the navbar) and the text will be hidden automatically.

Experience section

This section will include three different areas of knowledge and badges to highlight specific skills. This section will be responsive and it will have a hover effect to add interactivity.

Projects section

This section will include links to the GitHub repositories and to the live versions of the projects. We will create this section with the Bootstrap grid, so it will be fully responsive and you will learn to work with grid breakpoints.

Articles Section

A list of articles or blog posts. These will be Bootstrap cards and list groups. Each article will be represented by a link that will be opened on a new tab.

Testimonials Section

A clients testimonials carousel. This will be a Bootstrap carousel component with three testimonials and controllers to move to the previous or next item in the carousel.

This section will have links to social media profiles and it will show the copyright of the website. The social media links will be customized Bootstrap icons.

Behind the Scenes

We will work with:

The Bootstrap grid to adapt the website to devices of different sizes.
Bootstrap components, including buttons, carousel, responsive navigation bar, responsive images, cards, list groups, and more.
Bootstrap icons to add links to social media profiles (Twitter, GitHub, LinkedIn, and Instagram).
Semantic HTML tags such as
,
, and
.
Media queries to adapt the HTML elements to devices of different sizes and orientations.
CSS selectors
Google Fonts
More!

You will practice many different skills by building this project and when you complete it, you will have a fully responsive professional portfolio to showcase your skills.

Sounds awesome, right?

💡 Tip: after creating the basic structure of the website, you can customize it with your unique profile image, skills, and projects.

🔹 Development Tools

We will work with multiple tools that developers use in their everyday work.

Visual Studio Code

A powerful and popular code editor created by Microsoft. You can download and install it for free from its official website.

Visual Studio Code - Official Website

Live Server Extension for Visual Studio Code

A very helpful extension that will help us to improve our productivity by refreshing the browser when we change our HTML or CSS files.

Live Server - Documentation in the Extensions Marketplace

Chrome Developer Tools

A set of developer tools that come built-in with the Google Chrome browser. They are super helpful to test the responsiveness of the website, to select elements in the HTML structure, and to preview changes in the HTML and CSS files.

Chrome Developer Tools - freeCodeCamp

💡 Tip: we will download and install all the necessary tools during the course and you will learn how to work with them step by step.

🔸 Course on YouTube

Awesome. Now you know more about Bootstrap 5, about the importance of creating a professional portfolio. You also saw what you will learn during the course.

If you are ready, we invite you to start taking the course on the freeCodeCamp Español YouTube channel:

💻 In this link, you can access the live project (in Spanish) and practice how to use Chrome Developer Tools.

✍️ Course created by Estefania Cassingena Navone (Twitter: @EstefaniaCassN, YouTube: Coding with Estefania).

I really hope you like the course and find it helpful to create your developer portfolio.

You are also welcome to continue learning with our Spanish courses:

Best Free Resources to Learn Golang – Go Coding Courses

freeCodeCamp — Tue, 11 Oct 2022 23:11:17 +0000

By Avdhoot Fulsundar

Golang has been around for a while now, and it's become quite popular among developers.

It is a simple yet compelling programming language that's well-loved because of its powerful features like concurrency and the fact that it is developed by Google.

Golang is a server-side language that's used in many fields like Data Science, Cloud-Native development, game development, and others.

Big companies like Google, Netflix, and Twitch use Golang, which is one of the reasons you should learn it, too.

Here are my top 5 recommended resources for you to learn Golang. If you want to learn more about Go in general, check out this freeCodeCamp article.

Learn Go Programming by Building 11 Projects – Course by FreeCodeCamp

Learning how to code by building projects is the best and fastest way to become an expert in that technology. This Golang course is completely free, and it's designed by Akhil Sharma and published on freeCodeCamp’s YouTube channel.

It covers pretty much all the topics you need to start developing projects in the Go language, and you get valuable content worth a lot for free in just one video.

You'll build the following projects in this course:

Simple Web Server
CRUD API
YSQL Book Management System
SlackBot to Calculate Age
Slackbot for File Uploading
Email Verifier Tool
AWS Lambda
CRM Fiber
HRMS Fiber
Complete serverless stack
AI Bot with wolfram and wit.ai

Check out this free course here and start learning Golang.

Golang Interactive Course by StudyTonight

Studytonight provides an interactive way to learn the Go language without installing any extra software. You just need a browser to start the course and you will be learning Golang by actually writing the code.

You will need 7500 coins to take the course, which you can earn by completing other courses for free. You will learn topics like:

Types and Variables
Operators, Conditionals, and Loops
How to Take User Input
Functions
Pointers, Arrays, and Slices
Maps, Structures, and much more.

Start your journey of the Go language with this interactive course here.

Effective Go

Effective Go is a free resource to learn the Go programming language and it is available on the official website of Golang.

This course provides an explanation of all the key concepts in the Go programming language, how to use them, and their syntax.

This guide provides everything from formatting to how concurrency works in Golang. You should check out Effective Go to get an in-depth idea of the Go language.

Visit Effective Go here to learn the Go language.

Go / Golang Crash Course by Traversy Media

This Go language crash course explains all the fundamentals of Golang. Brad Traversy covers all the basic knowledge you need to advance your Go language skills in just 90 minutes.

You don't need any knowledge of Golang if you want to get started with this course. All the codes and programs you are going to practice are already stored in this GitHub Repository.

This is one of the best Golang courses and it has helped many developers to learn the basics of Golang. Brad also helps you set up your Golang environment.

You'll learn fundamentals like:

Variable and Types
Packages
Functions
Arrays / Slices
Conditionals Loops
Maps
Range Pointers
Closures
Structs
Interfaces
Web and many more.

Gophercises

Gophercises gives you hands-on experience with the Go language by building beginner to advanced-level projects.

This free course contains 20+ projects for you to build from mini-applications to tools and packages. I've completed some of these projects and they helped me to sharpen my Golang skills.

You will not only learn how to code in Golang but how to read standard docs and learn from them, too.

You will practice Golang concepts like:

Channels
Mutexes
Goroutines
Functional Options
Chaining Interfaces
Various parts of the standard library (io, time, and many other packages)
Reading input from the command line

Check out Gophercises here and build fun projects!

Wrapping Up

Go programming language is easy to learn and it's one of the most popular programming languages out there right now.

If you want to upgrade your skills and become more successful as a developer, then Golang is a must to learn.

Try these Resources to learn the Go language and start taking advantage of this opportunity. All the best and have fun!

Free Coding Bootcamp – Learn to Code with Class Central + freeCodeCamp

freeCodeCamp — Wed, 03 Aug 2022 16:48:08 +0000

By Jessica Rose

In 2021, the Class Central team helped my friend and me teach three cohorts of free programming bootcamps based on freeCodeCamp curricula.

We’ve been joined by over 20,000 learners from around the globe and it’s just been an honor and a delight to get to learn along with so many learners.

Ramón and I had such a nice time teaching that we wanted to come back for another cohort. Starting September 5th we’ll be teaching another free 6-week bootcamp built around freeCodeCamp’s Web Development and JavaScript curricula.

How Does the Bootcamp Work?

Just like the last bootcamps, we’re supporting learners with livestreams looking at the lessons and giving you a chance to ask questions in real time.

Don’t worry if we’re not streaming in line with your schedule – all videos will be available on-demand. We also have some great guest speakers to add extra context, a community supported forum, and a lively (and well moderated) Discord community.

These courses are designed for part-time remote learners, and most of our learners spent 5-20 hours a week on their bootcamps. While it is possible to take both courses at the same time, we (gently!) suggest doing only one at a time, to help keep the workload comfortable for you as you learn.

We’ve tried to design the learning experience to be lightweight and enjoyable. There’s no tests to get in, no taking attendance, and nothing bad will happen if it takes you longer than 6 weeks to get through the course material.

We're continuing to refine how we teach and how we support our learners. If you wanted to join and learn with us you can sign up for the web dev course here or the JavaScript course here.

What Will You Learn?

These courses will cover everything in the freeCodeCamp Responsive Web Design and JavaScript courses.

This means that the Web Development bootcamp will teach:

HTML fundamentals: syntax, elements, images, links, lists, forms, buttons.
CSS: selectors, classes, ids, attributes, fonts, colors, sizing, positioning.
Accessible and responsive web design: websites for all and on all devices.
CSS layout tools: positioning elements with CSS Flexbox and CSS grid.

And the JavaScript course will cover:

Programming fundamentals: syntax, variables, operations, loops, functions.
Data structures: arrays, multidimensional arrays, array methods, objects.
Algorithms: searching, sorting, reversing, merging, splicing, hashing.
Object-oriented programming: methods, constructors, prototypes, inheritance.
Functional programming: terminology, constraints, mapping, filtering.

How is this Course Different from Paid Bootcamps?

Our free bootcamps are designed to support as many learners as possible, so we aren't able to offer as much 1:1 learner support. We do a lot more peer supported learning and are introducing paid mentors to help better support learners this time around. We also aren't able to offer career placement support due to the scale of these courses.

The most exciting difference is that these courses are free. Paid bootcamps can cost $10,000 or more. We've designed these courses so that you can save your money for important things like rent and video games.

How is the Bootcamp Free?

Great question! Ramón and I are volunteering our time because we love to teach.

The Class Central team is supplying the platform and paying for mentors because they're passionate about access to technical education.

And freeCodeCamp is supplying the curriculum for free because that's their mission.

How Can We Make the Course Better?

As an instructor, I'm always excited to learn more about how we can better support learners. I'm especially interested in how we can better support learners whose first language isn't English or who have hardware challenges.

If you do join the course, please do tell us how we can be better working to serve you. We won't be able to do everything everyone needs, but hearing more about how you learn will help us all.

10 Best Computer Science Courses to Take in 2022

freeCodeCamp — Tue, 08 Mar 2022 15:23:25 +0000

By Elham Nazif

Are you looking for the best introductions to computer science? I’ve ranked the top courses available online, following a robust methodology. And they're all free to audit. You can read about it below.

But if you’re in a hurry, here are my top picks. Click on one to skip to the course details:

Rank & Course	Workload	In Brief
1. CS50's Intro to Computer Science (Harvard)	100–200 hours	Comprehensive, super high-quality survey of CS.
2. Computational Thinking for Problem Solving (Penn)	70 hours	Getting the problem-solving mindset and methods.
3. Intro to Computer Science and Programming Using Python (MIT)	80–140 hours	Comprehensive CS survey through the lens of Python.
4. Principles of Computing (Rice)	40 hours	Hands-on overview of CS fundamentals, like probabilities.
5. Computer Science 101 (Stanford)	36 hours	Survey of major CS topics, including networking.
6. How Computers Work from Coursera (UoL)	40 hours	Bottom up view of computer functioning.
7. CS50's Understanding Technology (Harvard)	36 hours	Tech basics, if you aren’t ready for the main CS50.
8. Intro to Theoretical Computer Science (Udacity)	25 hours	Complexity and computability theory.
9. Mathematics for Computer Science (UoL)	40 hours	Comprehensive math overview for CS.
10. Mathematics for Computer Science (University of Hull)	9 hours	Great math intro if you’re starting from scratch.

What is Computer Science?

The definition of computer science is almost as broad as the definition of physics. So, to say that computer science is the study of computers and computing concepts is just as 'useful' as saying that physics is the study of nature and its phenomena.

Instead, I’ll tell you the main subfields of computer science that most universities include in their syllabus.

Computer architecture and organization naïvely ponders: ‘How do I design a computer?’
Programming steps in and questions: ‘But how will the computer understand the human?’
Operating systems interjects: ‘Hold on, how should the human interact with the computer?’
Data structures and algorithms chirps in: ‘After you've figured that out, how do we store and compute data efficiently?’
Networking and communication waits politely before inquiring: ‘So that’s all cool, but how can we make computers talk to each other?’

You get the gist. I’m sure you’ve had one of these intriguing thoughts pop up in your mind before. Luckily, these are the questions that computer science tries to answer.

By studying computer science, you can become a better programmer. Just as a veterinarian is likely to understand animals better than the average pet owner, by studying computer science, you can get a better grasp of the features, abilities, and limitations of these awesome code-running machines that we call ‘computers’.

Course Ranking Methodology

I followed a three-step process to build this ranking:

First, let me introduce myself. I’m part of Class Central, the leading search engine for online courses. I (@elham) built this ranking in collaboration with my friend and colleague @manoel, following the same approach we used with some success in our previous rankings of the best Python courses and best machine learning courses. At this point, I’d say it’s a pretty robust method.

We started building this ranking by looking at our database of 50K+ online courses. We were interested in things like ratings, reviews, and course bookmarks. This allowed us to make an initial selection. So this phase was purely data-driven.

This tentative first step rapidly helped surface some of the best options available out there. Word of mouth is very effective in online learning. Good courses get noticed. And the very best gather a lot of attention, and raving reviews.

That said, reviews don’t always tell the whole story. In fact, some courses are so good at grabbing the spotlight early on that other excellent resources can go unnoticed. So the next step was to bring our personal knowledge of online education into the mix.

Second, we used our experience as online learners to evaluate each of our initial picks.

We both come from computer science backgrounds and are prolific online learners, having completed about 45 MOOCs between us. Additionally, Manoel has an online bachelor’s in computer science, and I am currently completing my foundation in computer science.

Manoel gathered the courses while I wrote the article you’re currently reading. Throughout this process, we bounced ideas off each other and made iterative improvements to the ranking until we were both satisfied with the end result.

Third, during our research, we came across courses that felt well-made but weren’t well-known. If we adopted a purely data-centric approach, we would have to leave those courses out of the ranking, if only because they had fewer enrollments and ratings.

But no. This ranking is deliberately opinionated and holistic. When we felt confident that a course was worth including, even when the course might not yet have quite as many reviews as some of its competitors, we went with our gut and included it.

We also spiced up the list by including a wide variety of computer science courses that will hopefully cater to the diverse range of learners, whether you’re a true beginner or someone with some foundations in computer science, or an interest in specific topics like math.

After going through this process — combining Class Central data, our experience as lifelong learners, and lots of editing — we arrived at our final ranking. So far, we’ve spent more than 10 hours building this ranking, and we intend to continue updating it in the future.

Course Ranking Statistics

Here are some aggregate stats about the ranking:

In total, the courses in this ranking accumulated over 5 million enrollments with 2 courses having over 1 million enrollments each.
The most popular course in the list has 3.5 million enrollments.
All of the courses in this ranking are either entirely free, or free to audit.
With 4 courses each, edX and Coursera are tied for the most represented provider in this ranking.
Around 480k people are following Computer Science Courses on Class Central.

Without further ado, let’s go through the top picks.

1. CS50's Introduction to Computer Science (Harvard University)

Course instructor Prof. Malan with his students

My first pick has to be CS50's Introduction to Computer Science, offered by Harvard University on edX. Launched on edX in 2012, CS50 is the computer science course on the internet. It is famous for its splendid production quality and its yearly curriculum updates.

It provides a succinct but comprehensive overview of what computer science is all about. Whether you are a newbie who has never heard of ‘Hello World!’, or a programmer who knows a thing or two about computers, you’ll come out of this course having learned something new.

One Thing to Note

Although the course exercises come in two versions, easy and challenging, I found that even the easy exercises can be a bit tricky. If you know nothing about programming, I’d recommend you find someone to study this course with.

Fortunately, CS50 has one of the largest and most active course communities online: check their Discord.

Or if you’re looking for a shorter, more practical course, you might want to have a look at my Python ranking, which includes some gentler on-ramps into the world of programming.

The Instructor

We can't discuss CS50 without bringing up David J. Malan, the Harvard professor that teaches the course. Rarely has an instructor been so instrumental to the success of a course.

Beyond being an excellent educator, Prof. Malan is a true entertainer, with near-perfect delivery. And when you’re tackling an academic course that may take you dozens of hours to complete, having an instructor capable of capturing the learner’s attention makes a huge difference.

So if despite a sincere desire to learn, you find yourself falling asleep while taking online courses, this might just be the course for you. Prof. Malan’s energy is contagious!

What You’ll Learn

The course begins with the premise that computer science is, at its core, problem solving. It introduces you to binary, the fundamental language of computers, and explains how sequences of 1s and 0s can somehow represent text, images, videos, and even sounds.

You’ll learn that algorithms are step-by-step instructions designed to solve a problem. The most common type of algorithms you’ll deal with throughout the course are algorithms for sorting and searching, like bubble sort, merge sort, and binary search.

You may wonder, ‘What’s the point of having many different algorithms if they all do the same thing?’. This is when you’ll learn about measuring the efficiency of an algorithm with Big O notation.

The first programming language the course teaches is the beginner-friendly language Scratch. Through block-based coding, you'll use Scratch to illustrate fundamental programming concepts like functions, conditional statements, boolean expressions, loops, and variables.

Later in the course, you’ll notice that these fundamental concepts keep coming up time and again, since they can be found in pretty much every programming language that CS50 will teach you.

The course then removes your training wheels and drags you down into the depths of low-level programming languages. By “low-level”, I don’t mean “less valuable”. In computer science, low-level programming languages are languages that are close to machine code: the closer they are to machine code, the “lower” they are.

Assembly language is as close as we get to binary, and the course will briefly discuss it. But our first deep dive into traditional programming (writing lines of code instead of arranging colorful blocks like with Scratch) will be with C, a low-level programming language where you'll manage memory by hand and implement your first data structures.

You’ll learn that computers store data in sequences of locations in memory, and how computers can locate and access data with addresses and pointers. You’ll also learn about the different ways we can create and store lists of values, like arrays, linked lists, and trees.

You’ll compare the advantages and disadvantages of each data structure. For example, hash tables can be accessed in constant time, but require mitigating the risk of data collision.

You’ll then be brought back up to the surface towards “higher-level” programming, where you’ll be able to comfortably breathe as you begin working with Python, and continue jumping from topic to topic.

You’ll explore SQL, the programming language of many databases. The final weeks of the course culminate in you building and designing an interactive website with HTML, CSS, JavaScript, and a Python framework called Flask.

How You’ll Learn

The course is ten weeks long, plus an open-ended final project that might take an extra week (or more, if you want to work on something really ambitious).

The course is recorded annually on-campus at Harvard before being launched online the following Spring. While the recording is ongoing, you might be able to join via live stream with a hundred other learners, or if you live near campus, even attend in person — though the pandemic might preclude this for the foreseeable future. Otherwise, you’ll have access to on-demand recordings on edX or via Harvard OCW.

Regarding assessments, you’ll complete ten problem sets, eight labs, and a final end-of-course project that you’ll have to design and come up with yourself or with a team. You’ll be able to code and submit these via a convenient in-browser VS Code-based editor.

Institution	Harvard University
Provider	edX
Instructors	David J. Malan, Brian Yu
Level	Beginner
Workload	100–200 hours total
Enrollments	3.4M
Certificate	Free and Paid (see below)

CS50 Lineup

A lot of people have heard about CS50’s Introduction to Computer Science, but not many realize that there are 10 other courses under the CS50 brand. A few follow-up courses worth mentioning are:

What’s even better: many of these courses offer a free certificate. If you’d like to know more about the CS50 courses, and how to get a free certificate, you can read Manoel's CS50 guide.

Fun Facts

The course instructor David J. Malan has been teaching CS50 for 15 years, first on-campus at Harvard, and on edX since 2012.
CS50 has been bookmarked around 30k times and has over 100 reviews on Class Central.
Every year, CS50 organizes Puzzle Day, a friendly problem-solving competition where you’ll have the opportunity to collaborate with learners worldwide.
CS50 is a part of both our list of most-popular courses of all time and best free courses of all time.
David J. Malan was the founder and chairman of Diskaster, a hard drive and memory card data recovery firm. One of the exercises in the course is a nod to his previous work.
CS50 is the longest course on this ranking, owing to its comprehensiveness.

If you're interested in this course, you can find more information about the course and how to enroll here.

2. Computational Thinking for Problem Solving (University of Pennsylvania)

The course instructors, Susan Davidson and Chris Murphy

My second pick would be Computational Thinking for Problem Solving from the University of Pennsylvania on Coursera.

This course focuses on the skills underlying computer science — computational thinking.

Computational thinking is the process of breaking a problem into parts, and then coming up with a resolution method that can be carried out by a computer.

Once you’ve embraced computational thinking, you’ll be in the right mindset to tackle additional computer science courses. So you could see this course as a foundation before the foundation. That said, if your interest lies in problem solving per se rather than CS as a whole, this course should also be a great fit.

You do not need any prior experience with computer science or programming to take this course, although some basic high school mathematics would be useful.

What You’ll Learn

The course covers four main topics: computational thinking, algorithms, computer architecture, and Python.

First, the course outlines the four pillars of computational thinking. You’ll begin with decomposition, breaking down a complex problem into smaller, simpler problems. Then through pattern recognition, you’ll compare the problem to other similar problems that have been solved previously.

Afterwards, during data representation and abstraction, you’ll simplify the problem even more by identifying what characteristics of the problem are important and filtering out those that are not.

The last pillar of computational thinking, algorithms, forms the second section of the course. The course defines algorithms as a set of step-by-step instructions to solve a problem. With algorithms, you can teach the computer how to solve problems without explicitly telling them precisely how. Instead, your algorithm will be able to handle a number of different cases, as long as these satisfy some preconditions.

You’ll explore a variety of algorithms, like linear and binary search. You’ll learn how to represent algorithms with flowcharts, analyze the complexity of algorithms (Big O), and calculate the number of possible solutions to an optimization problem. Lastly, you’ll compare the benefits and limitations of common algorithmic approaches to problem solving.

The third part of the course gives a brief history of computers, before settling on the computer architecture used by modern computers — the Von Neumann Architecture.

It consists of three fundamental units: the memory, CPU, and I/O. You’ll learn how data and instructions are stored and accessed in computers as bits and bytes, and also how executing code amounts to moving pieces of data in memory and operating on it in the CPU.

In the fourth and final section, the course will instruct you on the basics of Python programming. You’ll explore iterations, classes, and debugging. And you’ll end the course by coding your own Python program, where you’ll get to implement the algorithms you learned previously into code.

How You’ll Learn

The course is 4 weeks long, with each week having about 18 hours of course material. You’ll learn primarily from video lectures, and after each video there’ll be a short quiz to test your recall. There is supplementary material available on math, for those not-so-confident in their mathematical abilities.

At the end of each week, you’ll be presented with a case study where you’ll see examples of computational thinking used to solve real-life problems. Afterwards, you’ll complete a project where you’ll apply what you’ve learned. Do note that the assessments in this course are for verified learners.

Institution	University of Pennsylvania
Provider	Coursera
Instructors	Susan Davidson and Chris Murphy
Level	Beginner
Workload	70 hours total
Enrollments	74K
Rating	4.7 / 5.0 (1K)
Certificate	Paid

Fun Facts

This course is endorsed by Google, which decided to make it part of its Digital Garage, a collection of courses and resources for learners wanting to gain tech skills.
Penn’s Prof Susan Davidson, the course instructor, was named a Fellow of the American Association for the Advancement of Science in 2021.
Prof. Davidson also teaches some of the courses of Penn’s Master of Computer and Information Technology (MCIT), which is offered online through Coursera.

If you're interested in this course, you can find more information about the course and how to enroll here.

3. Introduction to Computer Science and Programming Using Python (Massachusetts Institute of Technology)

Prof. Eric Grimson, course instructor

My third pick for the best computer science course is Introduction to Computer Science and Programming Using Python, offered by MIT on edX.

This course approaches the field of computer science and programming through Python. The course focuses on breadth rather than depth, giving students background knowledge on the numerous applications of computation.

So this course is similar to our first pick in that it’s a survey course: it covers a lot, but not in great detail. But it’s dissimilar in that it focuses entirely on one programming language, Python, while Harvard’s course involves multiple languages.

Depending on your goals, this focus on Python could be seen as a positive or a negative. For what it’s worth, I believe Python is an excellent first programming language.

Heads up! This course tries to mirror the MIT on-campus experience, so don’t expect it to be a cakewalk. You won’t need any prior experience with computer science or programming to take it, but you’ll need a background in high school mathematics.

What You’ll Learn

The main topics the course explores are computational thinking, data structures, iteration and recursion, decomposition, abstraction, and algorithms and complexity.

You’ll be given a brief introduction to computation and computational thinking. You’ll learn what computers are, how they work, and what their limitations are.

By understanding that computers only know what you tell them (and what they can infer from what you tell them), you’ll realize that in order for the computer to accomplish a task, they need a ‘recipe’ containing a sequence of instructions they should follow. This is what computer scientists call an algorithm.

Your programming journey begins by learning Python and its basic syntax. With Python, you’ll explore concepts common to most programming languages. These include variables, conditional statements, and control flows.

Furthermore, you’ll be introduced to functions and the role they play in decomposition, abstraction, and recursion, which are concepts fundamental to problem-solving in computer science.

By then, you should be able to code simple programs that can come up with approximate solutions to difficult math equations through a guess-and-check method.

Lastly, you’ll learn about the different ways we can represent information in Python, called data structures. You’ll work with lists, tuples, and dictionaries, and understand when to use one data structure over another.

How You’ll Learn

The course is 9 weeks long with an expected workload of 14 to 16 hours each week. The main mode of learning is video lectures, and the course includes plenty of activities to put your hard-earned skills into practice. You’ll also have access to a learner’s forum where you can discuss with fellow learners.

There are 3 problem sets containing challenging coding exercises that will help you solidify your knowledge. If you are a verified learner, you’ll have to complete a timed mid-term and final exam in order to receive your certificate.

Institution	Massachusetts Institute of Technology
Provider	edX
Instructors	John Guttag, Eric Grimson, Ana Bell
Level	Intermediate
Workload	80–140 hours total
Enrollments	1.5M
Certificate	Paid

Fun Facts

This course has over 18k bookmarks and 120 reviews on Class Central.
It is the first of a two-course XSeries Program on edX. The second is Introduction to Computational Thinking and Data Science, which could make for a good follow-up.
One of the instructors, Professor John Guttag, leads the Data Driven Inference Group at MIT’s legendary Computer Science and Artificial Intelligence Laboratory (CSAIL).

If you're interested in this course, you can find more information about the course and how to enroll here.

4. Principles of Computing (Part 1) (Rice University)

Prof. Scott Rixner, course instructor

Principles of Computing (Part 1), by Rice University on Coursera, is my fourth pick for the best computer science introduction. The course emphasizes doing rather than watching, requiring you to complete many coding assignments.

This course aims to help you step up your programming skills by teaching you computational problem solving, a skill that underlies computer science, and that was also the focus of our second pick. This will involve learning important programming practices and developing a mathematical foundation for problem solving.

To take this course, you’ll need to be comfortable with writing small (100+ lines) programs in Python, as well as have some background in high school mathematics. So this one doesn’t start from scratch, and is therefore geared toward learners that also have some basics down.

If you’re looking for a problem solving course with fewer prerequisites, you might want to have a look at our second pick.

What You’ll Learn

The course includes refreshers on Python, code testing, probability and randomness, combinatorics, and function growth.

After a brief review of Python, the course will explain how to build tests, and why having tests for your Python programs can be useful.

Many programmers dislike or don’t simply bother to write tests for their code, but as one of the instructors explains, it’s a best practice worth treating as an integral part of the programming process.

Writing tests will help you save time and effort, and serves as a reusable sanity check that your program actually does what it’s supposed to do. For your first mini-project, you’ll recreate the well-known game 2048 in Python.

Then, the course moves on to the role of probability and randomness in computer science. You’ll learn how to identify unreasonable outcomes in probability, along with calculating the expected value of multiple outcomes.

For example, what’s the chance that a die would roll seven sixes out of ten tosses? And if that were to happen, to what extent could we conclude that the die is weighted — that is, that the rolls were unfair?

You’ll also see how we can use Python to simulate the probability of outcomes, a valuable tool used in statistical modeling. And for your second mini-project, you’ll work with probabilities to create an opponent that you can face in a game of Tic-Tac-Toe.

The course also touches on combinatorics, which deals with enumerations, permutations, and combinations. You’ll figure out how to calculate the total number of ways an event can play out.

This helps greatly in calculating the number of steps an algorithm would take, thereby allowing you to estimate the running time of the algorithm, and in turn, determine if the algorithm would be worth implementing. You can see why combinatorics plays a major role in password and computer security. For your third mini-project, you’ll code the familiar dice game Yahtzee.

In the final part of the course, you’ll be taught the importance of counting in solving complex problems. Counting answers the question of how long an algorithm might take to run given a task. Another name for counting you might be more familiar with is “time complexity”.

You’ll also learn about higher-order functions in Python, that is functions that take other functions as algorithms, like the map function. In your last mini-project, you’ll use these concepts to make your own version of Cookie Clicker.

How You’ll Learn

The course is split into 5 weeks, with each week involving 7 to 10 hours of study. You’ll learn primarily through video lectures and graded assignments, although the course does supply supplemental notes and activities for further reading and practice.

You’ll code and submit the homework and mini-projects on their companion website CodeSkulptor, and in-browser code editor that will preempt the need of setting up a local coding environment.

Institution	Rice University
Provider	Coursera
Instructors	Scott Rixner, Joe Warren, Luay Nakhleh
Level	Intermediate
Workload	40 hours total
Enrollments	30K
Rating	4.7 / 5.0 (600)
Certificate	Paid

Fun Facts

The course has around 15k bookmarks on Class Central.
This course is the third of seven courses that make up the Fundamentals of Computing Specialization. Upon receiving the specialization certificate, you’ll have completed 20+ projects, including a capstone project.
If you’re not interested in taking a full specialization after this course, but you’d like to learn more about the course topic, as the course name implies, there’s a follow-up course: Principles of Computing (Part 2).
Course instructor Prof. Scott Rixner is faculty director of two online degree programs at Rice University. So his dedication to online education extends beyond the scope of his own MOOCs.

If you're interested in this course, you can find more information about the course and how to enroll here.

5. Computer Science 101 (Stanford University)

Prof. Nick Parlante, course instructor

Computer Science 101 aims to demystify the magic of computers by demonstrating that they work by following a few relatively simple patterns.

This course will help you become familiar with those patterns. It will give insights into how computers work and what their limitations are.

In addition, the course delves into networking and other major topics within CS. No prior knowledge of computer science required!

What You’ll Learn

The course starts off with the fundamental equation of computers: Computer = Powerful + Stupid. Computers are powerful because they can perform billions of operations per second. But they are stupid because they need someone to tell them what to do. This is where programmers come into play.

This course uses small snippets of JavaScript to introduce you to programming and other computer science concepts. You’ll gain a grasp of programming concepts like variables, loops and iterations, conditional statements, and so on. The course later covers low-level and high-level languages, as well as compilers and interpreters.

The computer is a tool and the programmer wields the tool. Therefore, to program efficiently, it is important to understand how the tool works. The course covers many aspects of said tool, including hardware. You’ll learn about the parts that make up a computer, and look at how computers can represent different information formats.

The main format you’ll work with is images. One of the things you’ll do is “greenscreen” images as well as turn coloured images into grayscale by operating at the individual pixel level.

Another topic the course covers is computer networks, which is how computers communicate with one another. You’ll learn about the different types of networks.

You’ll study what IP addresses are and how they allow computers to locate each other. The course discusses how computers transmit information through data packets, and also the communication protocol the Internet runs on — TCP/IP.

The course also briefly covers a variety of other topics like databases and spreadsheets, computer security, and analog and digital data.

How You’ll Learn

The course is 6 weeks long, with each week taking 4–6 hours to complete. Lessons are provided through video lectures and are supplemented with notes and assessments. However, you’ll need to be a verified learner to access the assessments.

Institution	Stanford University
Provider	edX
Instructor	Nick Parlante
Level	Beginner
Workload	36 hours total
Enrollments	100K
Certificate	Paid

Fun Facts

The instructor acknowledges Google for supporting his early research into creating the class. I think this goes for all of us!
This course has 3k bookmarks on Class Central.
The course instructor Nick Parlante’s current interest is in CodingBat Java, an experimental online code-practice tool.

If you're interested in this course, you can find more information about the course and how to enroll here.

6. How Computers Work (University of London)

Dr. Marco Gillies, course instructor

This concise course taught by the University of London on Coursera touches on a few key topics in computer science, but it is mostly interested in helping you build a foundational understanding of hardware. It’s in the title really: by the end of the course, you’ll know how computers work.

And through that understanding, you’ll also form a clearer picture of how computers can be leveraged to help solve everyday problems.

The course is just as suitable for someone wanting to build solid foundations for further study in CS, as it is for someone simply curious about how computers work and wanting to explore some key CS topics but not necessarily a deep dive.

You do not need any prior knowledge of computer science to take this course.

What You’ll Learn

This course covers computer hardware, abstraction, modularity, computer networks and communication.

The course begins with abstraction — the art of drawing attention to the important details while filtering out the noise. Many disciplines rely on abstraction, and computer science does so heavily, both at the hardware and software levels.

This concept will become apparent when the course starts discussing computer hardware, like memory, CPU, and other devices. You’ll use notional machines as means for capturing these abstractions.

Afterwards, you’ll move on to another key idea: state and modularity. This will help you answer the question, ‘Why does turning off and on my computer fix most problems?’

Using notional machines, you’ll explain how computer applications function by transitioning through different states, and how modularity allows them to interact with other applications. You’ll learn how to debug stuff, a very useful skill indeed.

Moving on, you’ll learn how computers talk to one another over the Internet through networks and communication protocols. You’ll also learn about the kinds of security threats computers (and users) face, and how to protect yourself from malicious actors.

Lastly, you’ll explore basic web development. By applying your new-found knowledge of abstraction, state, and modularity, you’ll be able to clearly understand how websites work.

How You’ll Learn

The course is 4 weeks long, with 10 hours worth of material per week. It consists of video lectures and quizzes to test your knowledge of the material. You’ll have the chance to share your thoughts in discussion prompts.

Institution	University of London
Provider	Coursera
Instructor	Marco Gillies
Level	Beginner
Workload	40 hours total
Enrollments	25K
Rating	4.6 / 5.0 (440)
Certificate	Paid

Fun Facts

The course instructor, Prof. Marco Gillies, is the Academic Director of Distance Learning at Goldsmiths, University of London.
This course is an introduction to the University of London’s Online Bachelor of Computer Science, offered on Coursera.
It is course two out of three of the Introduction to Computer Science and Programming Specialization, with the first course being Introduction to Computer Programming.

If you're interested in this course, you can find more information about the course and how to enroll here.

7. CS50's Understanding Technology (Harvard University)

Prof. Malan (again!), course instructor

This is another course from the CS50 family. But unlike our first pick, which is the main CS50 course, this course is for those who work with technology everyday but don’t understand how it all works under the hood or how to solve problems when something goes wrong. And it’s also for those who don’t (yet) work with technology — most notably, computers — but would nonetheless like to understand its functioning.

The course aims to fill in the gaps in your knowledge of hardware, internet, multimedia, programming, and web development, preparing you for the technology of today and tomorrow.

This course has no prerequisites.

What You’ll Learn

The course begins with an introduction to the language of computers, binary. It explains how computers use binary to represent text and other information. Then, you’ll move on to the hardware of the computer: CPU, RAM and Main Memory. You’ll learn about the functions of each of these components.

The course discusses Internet and multimedia, and the technologies underpinning them. It’ll tell you how computers can find and talk with one another. You’ll learn about the common Internet protocol TCP/IP and more.

You’ll learn about the different data representations of multimedia, like audio, images, and video. There are many file formats and compression techniques – the course will give you an overview of some of the main ones.

Next, you’ll be taught how to stay safe on the Internet. You’ll discover several ways to protect your data and privacy. This section will include lessons on cookies, passwords, two-factor authentication, encryption, and more.

You’ll continue with the basics of web development. You’ll learn how web browsers access the web with HTTP requests. Have you ever seen a 404 or 500 error when trying to visit a webpage? You probably have. Well, in this course, you’ll learn what these errors mean. A brief overview on the languages that allow us to build and style web pages, HTML and CSS, is provided.

Last by not least, you’ll discover the basics of programming. You’ll primarily use the block-based language Scratch to explore concepts common to pretty much all programming languages, like variables, expressions, loops, and so on.

Additionally, to demonstrate what an algorithm is (and more specifically the divide-and-conquer paradigm), you’ll watch the instructor tear a phonebook into halves… I had to mention this because it is both very instructive and memorable!

How You’ll Learn

The course is 6 weeks long, with each week taking 2 to 6 hours to complete, depending on your prior familiarity with the content. Each week contains at least one hour of lecture.

Regarding assessments, you’ll have to complete an assignment for each of the six topics presented in the course to earn a certificate.

Institution	Harvard University
Provider	edX
Instructor	David J. Malan
Level	Beginner
Workload	36 hours total
Enrollments	100K
Certificate	Free and Paid (see below)

Fun Facts

After taking this course, you’ll be more than ready to tackle CS50, our #1 pick.
This course has 1.6k bookmarks on Class Central.
Another fact about David J. Malan, the course instructor: he is an active member of the SIGCSE, the arm of the ACM concerned with computer science education.

If you're interested in this course, you can find more information about the course and how to enroll here.

8. Intro to Theoretical Computer Science (Udacity)

Screenshot from the course

For those who have some familiarity with programming and algorithms, and want to further their understanding of problem-solving in computer science, this rigorous but insightful course might be what you’re looking for.

Offered by Udacity, Intro to Theoretical Computer Science explores what makes a problem ‘hard’ to solve, even for a computer. Then, it shows how to reduce and simplify these ‘hard’ problems to make them easier to solve through computation.

What You’ll Learn

The course covers two main areas of theoretical computer science: complexity theory and computability.

Complexity theory asks how much of its resources, like time or memory, will a computer require to solve a problem. Computability, on the other hand, asks if a computer can solve a problem at all, even when given more time and memory.

The course introduces you to a variety of real-world problems from telecommunication, bioinformatics, and finance. You will recognize what makes a problem challenging, and the value of recognizing such problems. This will prime you for understanding what NP-completeness is. Then, you’ll understand what makes a problem ‘hard’ to solve, and be able to prove it.

The rest of the course discusses what to do with the problem once we’ve proved that it is hard (or even impossible to solve).

One of the ways to overcome this obstacle is to employ efficient, intelligent algorithms. Another way is to accept that the problem may not be perfectly solvable, and instead find an approximate solution. And yet another way is to use randomness and probability to poke around and find a solution.

You’ll be able to describe and use these techniques in practical situations: the course discusses the theory but it’s also hands-on.

Lastly, you’ll move on to problems that no computer can ever solve in theory. You will learn about undecidability and recognize the limits of computability.

How You’ll Learn

The course is 8 weeks long, with a total 14 hours of video lectures. Some videos have a quiz to help you practice recalling what you’ve learned. There are 7 chapters, and at the end of each chapter you will complete a problem set to put your new-found skills to good use.

Finally, there’s a summative exam at the end of the course.

Provider	Udacity
Instructors	Sebastian Wernicke, Sean Bennett, Sarah Norell
Level	Intermediate
Workload	25 hours
Certificate	None

Fun Facts

This course has 2.2k bookmarks on Class Central.
One of the course instructors, Sebastian Wernicke, has spoken multiple times at TED.
To tackle this course, you may want to learn about algorithms first. The instructors recommend another Udacity course on algorithms as a refresher. In addition, good math foundations would be useful too. Check our picks below if needed.

If you're interested in this course, you can find more information about the course and how to enroll here.

9. Mathematics for Computer Science (University of London)

Dr. Sara Santos, course co-instructor

Offered by the University of London, this course introduces you to the mathematics and mathematical thinking computer scientists use in their work. What distinguishes this course from other math courses is its playfulness, with fun and interactive exercises.

More specifically, the course combines elements of algebra, analysis, and geometry — topics carefully picked to serve as the backbone of your computer science education.

The course discusses, among others, number bases, an essential topic to understand binary, and conversion between binary and other bases, such as hexadecimal. It explores numerical progressions, like the well-known Fibonnaci sequence. And it will touch on geometry and function graphing.

By the end of the course, you’ll have acquired the foundation needed to understand the math that underpins other computer science courses, and you’ll be ready to tackle more advanced mathematical topics.

The course assumes you know some high school mathematics as well as basic Python programming.

What You’ll Learn

The course investigates five main topics: number bases, modular arithmetic, sequences, series, graph sketching and kinematics.

The course begins with the study of number bases. You might know that binary is the number base used by computers. But did you know that computer scientists also use hexadecimals?

You’ll cover the key concepts of place values and number systems, which will involve converting between binary, hexadecimal, and decimal, as well as adding, subtracting, and multiplying them together. Oh, a cool thing that the course teaches you is steganography, the art of hiding messages in images!

Next, you’ll cover modular arithmetic. Have you ever wondered what “modulo 7” means? You’ll learn about the usefulness of congruence and modular arithmetic operations in computer science (psst, it can be used for encryption).

You’ll identify, describe, and compute sequences of numbers and their sums. You’ll study a special family of sequences called progressions, which consists of arithmetic and geometric progressions. You’ll learn how sequences can be used to generate random numbers. Additionally, you’ll be able to tell when a series converges (meets at a point) or diverges (approaches infinity)

Lastly, the course describes how to represent and describe space numerically using coordinates and graphs. You’ll see how graphs can help us visualize and transform functions like straight lines, quadratics, cubics, reciprocals and more. An example of modeling motion will be given: the field of mathematics called kinematics.

How You’ll Learn

The course is 6 weeks long, with about 40 hours worth of material. Each week comes with one or more quizzes, allowing you to learn by doing. However, you’ll need to pay for the certificate for the course autograder to mark your answers.

Institutions	University of London
Provider	Coursera
Instructors	Matthew Yee-King and Sara Santos
Level	Beginner
Workload	40 hours total
Enrollments	22K
Rating	4.1 / 5.0 (200)
Certificate	Paid

Fun Facts

It is the third and final course of the Introduction to Computer Science and Programming Specialization.
Dr. Sara Santos enjoys math busking, which seeks to surprise and amuse people on the streets with performances rooted in math.

If you're interested in this course, you can find more information about the course and how to enroll here.

10. Mathematics for Computer Science: Essential Skills (University of Hull)

Laura Broddle, course instructor, teaching Venn diagrams

If you have taken a look at the previous two courses but do not have the mathematical foundations to take them yet, this course can help you with the basics.

This course is a short course on mathematics skills for computer science, offered by the University of Hull on FutureLearn.

Meant for learners starting or considering studying computer science at the university level, this course covers Venn diagrams and set theory, algebra techniques, and vectors and matrices — all fundamentals concepts ubiquitous in computer science.

The course assumes no prior mathematical knowledge. You’re starting from scratch.

What You’ll Learn

Starting off with Venn diagrams and set theory, you’ll learn how “sets” (bags of objects, if you will) can be formalized and operated on. You’ll learn to reason about computations and objects of computation. Venn diagrams will help you visualize this type of reasoning.

You’ll then move on to algebra and its techniques. You’ll be given an overview of algebra (which could be described as doing math using variables instead of explicit numbers) and its use in algorithms and scientific computation. The course will teach you how to solve linear equations and quadratic equations using algebra.

The course ends with an overview of vectors and matrices. You’ll learn what vectors are, and why they are especially important in graphics programming. You’ll learn how we can represent vectors as matrices, and how to modify, transform, and invert matrices to solve complex problems.

How You’ll Learn

This course is 3 weeks long, with around 3 hours of material per week. You’ll learn primarily through video material, although there are discussion forums where you can discuss problems with fellow learners.

At the end of each week, there is a quiz that’ll help you strengthen your understanding of mathematical concepts and applications.

Institution	University of Hull
Provider	FutureLearn
Instructor	Laura Broddle
Level	Beginner
Workload	9 hours total
Enrollments	1.2K
Certificate	Paid

Fun Facts

The course instructor, Laura Broddle, joined the University of Hull in 2015 as a foundation math teaching fellow.
She also had visited a sister school in Uganda and was rated an outstanding teacher by Ofsted in 2013.

If you're interested in this course, you can find more information about the course and how to enroll here.

10 Best Python Courses to Take in 2022

freeCodeCamp — Mon, 28 Feb 2022 19:56:20 +0000

By Elham Nazif

If you want to learn Python, there are a lot of great resources out there.

But if you're specifically looking for the best online course to learn Python, then you've come to the right place.

In this article, I present a list of awesome Python courses ranked according to a proven methodology that you can read about down below 👇.

But if you want to skip the read, here are my top picks:

Programming for Everybody (University of Michigan)
Computing in Python (Georgia Institute of Technology )
An Introduction to Interactive Programming in Python (Rice University)
[Scientific Computing with Python (freeCodeCamp)](#Scientific Computing with Python (freeCodeCamp))
Crash Course on Python (Google)
Introduction to Computer Science and Programming Using Python (Massachusetts Institute of Technology)
Intro to Python for Data Science (DataCamp)
Object-oriented Programming in Python: Create Your Adventure (Raspberry Pi Foundation)
Using Python for Research (Harvard University)
Automate the Boring Stuff with Python Programming (Udemy)

What is Python?

Python is a general-purpose programming language that puts simplicity above all else. It eases the programming process by hiding the ugly details like memory management and code boilerplate, and instead opts for friendly, human-readable code. It is easy to understand, so it's one of the best languages for beginners to learn.

Its scope of application is wide — from creating games to making web apps. This versatility has made it incredibly popular. In fact, Python currently tops the TIOBE index, which ranks the most-used programming languages. And according to Stack Overflow, Python is the third most popular language after JavaScript and HTML/CSS.

Python is also the language of choice for machine learning and data analysis, with 70% of practitioners preferring Python over other similar languages.

Coincidentally, according to the World Economic Forum’s Future of Jobs Report, the demand for machine learning and data science specialists will be growing faster than for any other field through 2025.

Speaking of which, if you’re interested in machine learning, here's a ranking of the best machine learning courses available online.

Note that the current major version of Python is Python 3, and every course in this list uses Python 3.

Course Ranking Methodology

I followed a three-step process to build this ranking:

First, I’m part of Class Central, the leading search engine for online courses. We have a database of more than 50K online courses. So it seemed like the natural starting point.

Building a ranking alone is fine. But building it collaboratively is better. So I (@elham) built this ranking with my friend and colleague @manoel.

We started by leveraging the database to make a preliminary selection of Python courses, looking at things like ratings, reviews, and course bookmarks. So this was a purely data-driven step, relying on hard metrics to create an initial ranking that we could then iterate upon and expand.

Using this approach, some of the top picks rapidly became apparent, since the best Python courses tend to have rave reviews. But we didn’t stop there. Ratings and reviews rarely tell the whole story. So the next step was to bring our personal knowledge of online education into the mix.

Second, we used our experience as online learners to evaluate each of our preliminary picks.

We both come from computer science backgrounds and are prolific online learners, having completed about 45 MOOCs between us. Additionally, Manoel has an online bachelor’s in computer science while I am currently completing my foundation in computer science – so unsurprisingly, we’ve both used Python extensively during our studies.

Manoel gathered, analyzed, and ranked the courses and I wrote the article you’re reading right now. Throughout this process, we bounced ideas off each other and made iterative improvements until we were both satisfied with the end result.

Instead, we favored a holistic approach. We spiced up this list by including those courses: more personal picks that hopefully surprise those of you who have already seen or taken the more popular Python courses and are looking for something a bit different.

After going through this process — combining Class Central data, our experience as lifelong learners, and a lot of editing — we arrived at our final ranking. So far, we’ve spent more than 16 hours building this ranking, and we intend to continue updating it in the future.

Course Ranking Statistics

Here are some aggregate stats about the ranking:

Put together, the courses in this ranking have accrued 9 million enrollments, with 4 courses having over 1 million enrollments.
Coursera, with four courses, is the most-represented provider in the ranking.
The single most popular course in the ranking has around 4 million enrollments.
Eight courses are entirely free or free-to-audit. Two are paid.
These courses have accumulated 38k reviews at Class Central.

Now then, let’s move on to our picks!

1. Programming for Everybody — Getting Started with Python (University of Michigan)

Dr. Chuck, course instructor

My number #1 pick for the overall best Python course for beginners has to be Programming for Everybody, offered by the University of Michigan on Coursera. This course is the most popular Python course on Coursera, with close to 2.5 million enrollments — and for good reason.

The course serves as a friendly introduction to the world of programming. It assumes from the get-go that you have no experience whatsoever coding nor know how programs work. It then moves from concept to concept, helping you build a comprehensive understanding of the Python language.

To take this course, all you need is some basic arithmetic. After completing the course, you’ll be ready to tackle more advanced programming courses.

What You’ll Learn

The course doesn’t immediately start with programming, but instead starts with what you’ll be programming on: a computer.

What are the basic components of a computer? What is a program, and how does a computer understand it? Why is it so easy for a computer to not do what you tell it to do? These are the questions that you’ll be able to answer by the end of the first part of the course.

Afterwards, you’ll be shown how to install and run Python on your machine and how to choose a suitable code editor. And then, you’ll get to write code! You’ll be taught the vocabulary of Python, its unique “grammar”, as well as higher-level programming concepts.

You’ll know how to write variables and expressions to store and compute values, which can be of different data types. You’ll know how and why you can use conditional statements to specify branching conditions in your code. You’ll be taught about functions and arguments, and how to leverage them for code reuse. Last but not least, you’ll understand what loops and iterations do.

By the end of the course, you’ll know how to write a program that accepts user input, computes a result, and returns an output to the user. A complete experience indeed!

How You’ll Learn

The course is broken down into 7 weeks, with each week containing about 4 hours of video lectures and programming tasks. The lectures themselves are based on the book that can be found on the accompanying course website, and they’ve been translated into 9 languages, if English isn’t your strong suit.

Coding assessments, which usually have to be completed two or three times a week, are found on the same course website and will either be automatically graded or graded by another learner taking the course.

Institution	University of Michigan
Provider	Coursera
Instructor	Charles Severance (aka Dr. Chuck)
Level	Beginner
Workload	28 hours total
Enrollments	2.5M
Rating	4.8 / 5.0 (205K)
Certificate	Paid

Fun Facts

This course is the first of the five in the specialization Python for Everybody. If you’d like to round up your Python skills after finishing this course, here’s the next one in the series: Python Data Structures — which can also be audited for free.
If you'd like to take the whole specialization for free, with extra projects, and get a free certification on top, check out the fourth item in this ranking.
This course has over 123k bookmarks and 35k reviews on Class Central.
Dr. Chuck’s course is a part of both our list of most-popular courses of all time and best courses of all time. So yeah, this was an easy first pick.
The course instructor Dr. Chuck is a super popular instructor. If you like his teaching, be sure to check out his other courses on Django and Web Applications.

If you're interested in this course, you can find more information about the course and how to enroll here.

2. Computing in Python I: Fundamentals and Procedural Programming (Georgia Institute of Technology)

Dr. David Joyner, course instructor

My second pick for the best Python course would be Computing in Python I: Fundamentals and Procedural Programming, offered by the Georgia Institute of Technology on edX.

Although only basic arithmetic is necessary, Computing in Python is a robust course meant for learners who want to gain a comprehensive understanding of programming and beyond.

The course not only serves as an introduction to Python, but also to the fundamentals of computer science, exposing learners to concepts every programmer can benefit from.

The course is taught by Dr. David Joyner. As it happens, my colleague Manoel has taken four of his courses in the context of his online master’s degree, and he even met the guy. He only has good things to say about David Joyner and his courses, which are always carefully thought out, in particular in terms of instructional design and teaching methods.

The course is part of the Introduction to Python Programming Professional Certificate, which closely matches Georgia Tech’s undergraduate introduction to computer science, providing you with the skills needed to explore more advanced concepts and prepare for the professional world.

What You’ll Learn

The course starts with an introduction to computing and explains how computers work. You’ll learn the jargon of computing and understand how code processing works.

After setting up your programming environment, you’ll be introduced to the basic principles of programming, like the difference between compiling and executing code and the write-run-debug cycle. You’ll know how to analyze the results of running your code and use those results to revise it.

Next, you’ll be introduced to the paradigm of procedural programming in Python. The course makes you realize that a program is just sequences of lines of code that is executed to fulfill a purpose, and that programs can be chained to achieve more complex functionality.

Lastly, you’ll study variables, the different types of variables, and the role they play in programs. You’ll be introduced to mathematical, relational, and Boolean operators and understand how to use them to express complex relationships in code and even make “decisions”, such as running certain lines of code only if a predefined condition is met.

How You’ll Learn

The course consists of 5 weeks of material, and you are expected to spend 9–10 hours a week learning. The course comes with an online book that serves as a basis. Also, each week is dedicated to a specific area of computer science and programming. You are encouraged to skip areas you already know to make the best use of your time.

There are two kinds of assessments you’ll be able to complete if you audit the course for free: exercises and two practice tests. If you’re a verified learner, you’ll have access to chapter-level problem sets and complete a timed assessment at the end of the course.

Institution	George Institute of Technology
Provider	edX
Instructor	David Joyner
Level	Beginner
Workload	50 hours total
Enrollments	207K
Rating	4.8 / 5.0 (213)
Certificate	Paid

Fun Facts

The professional certificate this course is part of earned a Bronze Award for Computing & IT at the 2020 Reimagine Education awards.
The course has a whopping 4.8 out of 5.0 rating on Class Central, with several hundred reviews.
For all practical purposes, you'll be completing the same course that undergrad Georgia Tech students take for credit.

If you're interested in this course, you can find more information about the course and how to enroll here.

3. An Introduction to Interactive Programming in Python (Part 1) (Rice University)

Prof. Joe Warren, course co-instructor

My third pick for the best Python programming course is An Introduction to Interactive Programming in Python (Part 1), offered by Rice University on Coursera.

This course is designed to help students with very little to no computing background learn the basics of creating simple interactive applications in Python, although you’ll need some background in high school mathematics (hopefully you remember the Pythagoras theorem!).

What separates this course from others is that it is project-based, encouraging you to build and research things from scratch, an invaluable skill for developers in the real world.

A word of caution, though – this beginner course isn’t meant to be easy. The instructors say that you'll learn faster from doing hard things (which I’ve found to be true), so you’ll have to dedicate a significant amount of effort to complete the course.

What You’ll Learn

You’ll start the course by learning how to express arithmetic expressions in Python and how to assign values to variables. You’ll see that Python can be used as a calculator!

Next, the course introduces functions through both a programmatic and a visual perspective. This will give you an understanding on how functions work and how errors may arise from them. T

he instructor also gives tips on how to debug your code based on the results it’s producing. You’ll learn logical and comparison operators, along with conditional statements, and use these concepts to build a rock-paper-scissor-lizard-Spock game.

Moving on, you’ll be instructed on the basics of event-driven programming, which are essential to build games and applications. Then, you’ll learn what local and global variables are, which will culminate in you building a simple responsive graphical user interface for a number guessing game.

You’ll learn how to process strings given by the user and draw text and shapes on a canvas. You’ll use this concept to build a digital stopwatch that’ll keep track of time to the tenths of a second.

At the end of the course, you’ll recreate the classic game Pong in Python. Along the way, you’ll learn how to work with lists, how to read keyboard input from the user, how to draw and simulate the movement of the ping pong ball in your application, and how to keep track of who won and who lost. This will serve as testament to your ability to create applications with lots of moving parts.

How You’ll Learn

The course is split into 5 weeks, with each week involving around seven to ten hours of material, including a weekly project. The course comes with a companion website called CodeSkulptor, where you’ll run and submit your Python scripts.

Each week has two auto-graded quizzes and a weekly project that is peer-graded.

Institution	Rice University
Provider	Coursera
Instructors	John Greiner, Stephen Wong, Scott Rixner, Joe Warren
Level	Beginner
Workload	50 hours total
Enrollments	194K
Rating	4.8 / 5.0 (3.1K)
Certificate	Paid

Fun Facts

The course has 97.3k bookmarks and 3.3k reviews on Class Central.
This course is the first of seven courses that make up the Fundamentals of Computing Specialization. Upon receiving the specialization certificate, you’ll have completed 20+ projects, including a capstone project.
Dr. Scott Rixner, one of the course instructors, has worked and developed Python interpreters for both embedded systems and web browsers. He knows his stuff!

If you're interested in this course, you can find more information about the course and how to enroll here.

4. Scientific Computing with Python (freeCodeCamp)

Arithmetic formatter project on freeCodeCamp

Scientific Computing with Python, offered by the folks here at freeCodeCamp, is based on Python for Everybody, the Coursera specialization that includes this ranking’s #1 pick.

However, while the specialization on Coursera is paid, on freeCodeCamp you can earn a free certificate of completion.

In addition, the freeCodeCamp certification includes additional projects, so if you have completed Python for Everybody and you would like to apply your newly acquired knowledge, you’ll find here some hands-on opportunities to hone your skills.

What You’ll Learn

Apart from the material from Python for Everybody, you’ll work on five scientific computing projects. Scientific computing is most commonly needed in specialized and technical industries, like engineering or data science. In each project, you will be given some starter code and will be tasked with completing it.

The first project involves building an arithmetic formatter that aligns arithmetic expressions vertically, just the way you would if you were doing the calculations by hand. You will learn to parse strings, how to deal with edge cases, and also learn how to prettily format text in the command line.

The second project involves creating a time calculator. You will have to parse an initial time and weekday, add a particular duration to it (say 14 hours), and finally return the new time and day.

In the third project, you will make a budgeting app. By the end of the project you’ll understand how to create classes and attributes that serve as budget categories, and then print a graph in the command line representing the percentage spent per category.

For the fourth project, you are tasked with creating rectangle and square classes. These classes should contain the shape attributes as well as methods for calculating the area or getting a string representation of the shape. So you’ll really get to practice OOP, and in particular, inheritance.

Lastly, the fifth and final project requires you to write a function that can determine the probability of drawing balls of certain colors randomly from a hat. With object oriented programming, you will learn how to create a function with varied arguments, work with Python’s random module, and gain some insight into statistics and probabilities.

How You’ll Learn

The full 56 lecture set of Python for Everybody is available on freeCodeCamp. And after each lecture, you will be quizzed on what you’ve learnt from the video.

In total, the certification may take up to 300 hours to complete, but if you already know some of the rudiments of programming, it might take you half as long.

You’ll also create 5 scientific computing projects, each graded automatically.

Provider	freeCodeCamp
Instructor	Charles Severance
Level	Beginner
Workload	150 hours total
Certificate	Free

Fun Facts

As you may know, freeCodeCamp is a nonprofit that helps people learn to code by building projects, for free. They offer 10 courses with free certifications.
freeCodeCamp’s Youtube Channel has more than 5M subscribers and 1200+ videos on a wide variety of programming and computer science topics. (Yes, we’re fans)
If you’d like to support freeCodeCamp’s mission of providing free education, you can make a donation here.
More on Dr. Chuck: he is the Clinical Associate Professor of Information at the University of Michigan, and besides freeCodeCamp, his course is offered on Coursera, edX, and FutureLearn — so pretty much on all major platforms.

If you're interested in this course, you can find more information about the course and how to enroll here.

5. Crash Course on Python (Google)

Christine Rafla, Google system administrator

Crash Course on Python is offered by Google on Coursera as part of the Grow with Google initiative.

This course is a fairly comprehensive course on Python, teaching you most of the language’s features.

No prior experience with programming is needed for this course. By the end of the course, you’ll have an understanding of Python’s capabilities and be able to write simple programs in Python.

What You’ll Learn

You’ll start by learning about programming in general and why learning to automate things with your computer can be a time-saving skill.

Then, you’ll be introduced to Python and its features. For example, you’ll be able to identify, distinguish, and convert different types of data types in Python, you’ll learn what functions are and the role they play in code reuse, you’ll learn about the logical and comparison operators Python offers, as well as conditional statements. The course also teaches you how comments can help make your code cleaner.

Next, you’ll move on to more advanced topics like loops and iterations, and how to avoid creating infinite loops. A brief section on recursion — a fundamental (but tricky!) programming concept — is also included.

You’ll dive into common data types like strings, dictionaries, tuples, and lists. You’ll know how to extract certain values from them and how to modify them. There is also an optional section on object-oriented programming, where you’ll learn about classes and their instances, attributes, methods, and inheritance.

You’ll also learn about documenting with docstrings, how to navigate and use Jupyter notebooks, and how to import and use Python modules in your code. So yeah, this course packs a lot of information.

How You’ll Learn

The course runs for 6 weeks, with each week being 4 to 5 hours long. You'll learn through video lectures and supplementary notes, and practice what you've learnt in weekly exercises.

Regarding assignments, at the end of each week you’ll have to complete a graded assignment.

Organization	Google
Provider	Coursera
Level	Beginner
Workload	30 hours total
Enrollments	507K
Rating	4.8 / 5.0 (22K)
Certificate	Paid

Fun Facts

It is the first course out of six of the Google IT Automation with Python Professional Certificate.
The course has around 500K enrollments on Coursera, with about 22K reviews.
The Grow with Google Initiative this course is part of includes many other resources for online learners.

If you're interested in this course, you can find more information about the course and how to enroll here.

6. Introduction to Computer Science and Programming Using Python (Massachusetts Institute of Technology)

Prof. Eric Grimson, course co-instructor

If you read the course description page, you'll see that Introduction to Computer Science and Programming Using Python by the Massachusetts Institute of Technology on edX specifies that it is NOT meant to be an introduction to Python. So you might wonder why I included it in this ranking.

Well, learning Python is rarely the end goal in and of itself. You learn Python to be able to tackle coding projects, or as a stepping stone toward learning something else — for instance, computer science. If you're in that position, this course is an excellent pick for you.

The main aim of the course is to provide students with a brief introduction to a variety of topics in computer science, focusing on breadth rather than depth. This is to give students a sense of what is possible when thinking about using computation to accomplish specific goals, be it in your studies or career.

This course tries to mirror the on-campus experience at MIT, so it’s challenging and comprehensive. In terms of prerequisites, you want to have some knowledge of high school algebra and be willing to stomach some math, because this computer science course doesn’t shy away from that.

What You’ll Learn

The course starts off with a brief introduction to computing. It tells you what computers are, what they do, and some of their limitations.

It shows you the “recipe” of programming languages: how you combine low-level constructs like variables to build higher-order functionally, like full-fledged programs. And it dives into the features of Python, specifically.

Like in many other courses in this list, you’ll be taught about objects and data types in Python, and you’ll learn to construct simple expressions using mathematical, logical, or conditional operators.

You’ll also learn about the fundamental concept behind loops and iterations and how they are essential to building algorithms capable, for instance, of finding the solution to equations without being explicitly “taught” how to do so.

Moving on, you’ll learn about decompositions and abstraction and how functions serve to achieve those purposes and encapsulate functionality. You’ll know how to write a function and understand global and local scopes. You’ll understand recursion and how it relates to mathematical induction (you can even prove some cool theorems with this!).

At the end of course, you’ll get your feet wet in the data structures pool: you’ll learn about lists, tuples, and dictionaries. You’ll understand the intricacies of mutability, aliasing, and cloning these data types, as well as methods to operate on them.

How You’ll Learn

This course is 9 weeks long and you are expected to spend around 14 to 16 hours on lesson materials per week. The course has 6 chapters, each consisting of several lectures and multiple activities to apply your knowledge.

There are 3 problem sets, as well as a midterm exam and a final exam that you’ll have to complete if you want to earn a certificate.

Institution	Massachusetts Institute of Technology
Provider	edX
Instructors	John Guttag, Eric Grimson, Ana Bell
Level	Intermediate
Workload	144 hours total
Enrollments	1.5M
Certificate	Paid

Fun Facts

This course is the first of a two-course XSeries Program on edX. The second is Introduction to Computational Thinking and Data Science.
This course teaches you how to install Anaconda instead of the default Python installer. Anaconda is a great tool, most notably if you enjoy data science.
One of the instructors, Professor John Guttag, leads the Data Driven Inference Group at MIT’s legendary Computer Science and Artificial Intelligence Laboratory (CSAIL).

If you're interested in this course, you can find more information about the course and how to enroll here.

7. Intro to Python for Data Science (DataCamp)

Dr. Hugo Bowne-Anderson, course instructor

Intro to Python for Data Science, offered by DataCamp, is exactly what the course name states: it specifically teaches you Python for data science.

So if you’d like to learn Python with the ultimate goal of jumping into data science, or if you want to see what data science is all about, this could be an excellent course for you.

What You’ll Learn

Starting off with the basics of Python, you’ll learn about variables and the different data types. As precision of numbers is important in scientific calculation, you will be taught when Python implicitly converts types and how to explicitly do so.

Moving on, you’ll learn about lists and how to use them to store data. You’ll discover how to create lists and manipulate them by subsetting, extending, replacing or deleting their elements.

You’ll create functions and supply arguments to them. Additionally, you’ll be taught about the different methods that data types like strings and lists may have and how to use them.

At the end of the course, you’ll import your first Python package, NumPy. NumPy is a popular Python package used by data scientists and analysts. You’ll learn the difference between NumPy arrays and regular Python lists, and you’ll see how easy it is to compute and analyze data with NumPy.

How You’ll Learn

The course consists of 4 chapters, each about an hour long. After each lecture, you’ll have the chance to apply what you’ve learned in the exercises.

You’ll code using Datacamp’s in-browser programming environment, making it easy to get started with minimal setup.

Provider	DataCamp
Instructors	Hugo Bowne-Anderson, Vincent Vankrunkelsven, Filip Schouwenaars
Level	Beginner
Workload	4 hours total
Enrollments	4M
Certificate	Free

Fun Facts

This is one of the few courses on DataCamp that is completely free.
The course is just four hours long: unlike some of the longer courses in this ranking, this one is very much focused on Python basics, and it’s a refresher course too.
If after taking this course, you want to further explore data science, check out our list of the 10 Best Machine Learning Courses to Take in 2022.

If you're interested in this course, you can find more information about the course and how to enroll here.

8. Object-oriented Programming in Python: Create Your Own Adventure Game (Raspberry Pi Foundation)

Martin O'Hanlon, course co-instructor

Object-oriented Programming in Python: Create Your Own Adventure Game is for those who have the basic syntax of Python down and want to learn specifically about object-oriented programming, a popular coding paradigm supported by Python.

This course is offered by the Raspberry Pi Foundation on FutureLearn. By the end of the course, you’ll create your own text-based adventure game.

What You’ll Learn

The course begins by introducing you to objects, and explaining that pretty much everything is an object in Python. You’ll learn about the methods associated with each object, and use Python's turtle module to draw multiple shapes of different colors and sizes on a canvas.

Next, you’ll start to code your text adventure game, which will involve coming up with your own classes. You’ll learn about essential methods you can use to operate on instance attributes, like getters and setters — though Python is quite flexible in how it approaches this. Little by little, you’ll add “rooms” and “items” to your text adventure world.

You’ll also extend other people’s classes through concepts known as inheritance and polymorphism. For instance, you’ll add new attributes and methods to a “Character class” to make an “Enemy class” that your player can fight.

You’ll learn how to use diagrams to make sense of inheritance, a skill that could be useful later down the road if you ever find yourself planning larger-scale coding projects.

How You’ll Learn

The course runs for four weeks, with an average time of 2 hours of study per week. The course material consists of videos and accompanying articles.

FutureLearn is very social: you’ll have access to a dedicated forum under each article where you can discuss with other learners taking the course.

Organization	Raspberry Pi Foundation
Provider	FutureLearn
Instructor(s)	Laura Sach, Martin O'Hanlon
Level	Intermediate
Workload	8 hours total
Enrollments	54K
Rating	4.7 / 5.0 (133)
Certificate	Paid

Fun Facts

The course is based on the Teach Computing Curriculum.
The lead instructor, Martin O’Hanlon, is the co-author of a book that teaches you how to program in Python while having fun in Minecraft.
Raspberry Pis are awesome and have applications ranging from robotics to website hosting. The Pi Foundation also offers a getting-started course.

If you're interested in this course, you can find more information about the course and how to enroll here.

9. Using Python for Research (Harvard University)

Prof. Jukka-Pekka JP Onnela, course instructor

Using Python for Research, offered by Harvard University on edX, fills in the awkward gap between introductory and advanced Python courses for people in research who know some Python but are clueless on what to do with it.

This course introduces people to Python modules and concepts commonly used in scientific computation, such as NumPy and SciPy, as well as statistical learning. It allows learners to climb the ladder from a knower to a doer, and apply their skills in practical settings.

What You’ll Learn

The course starts with a basic review of Python 3, in order to bring everyone up to speed, in preparation for the following weeks. Before that, however, you are recommended to take a self-assessment quiz to see if the course is a good fit for you.

In week 2, you’ll start by studying scopes in Python. You’ll then jump into bona fide scientific computing with NumPy, learning about vectorization (an important optimization technique to process calculations in bulk), and you’ll create plots with matplotlib, a very popular visualization library in Python.

In weeks 3 and 4, you’ll explore specific examples of how Python can be applied in research — study cases, if you will. This exploration will involve topics such as DNA translation, language processing (NLP), classification problems, studying bird migration with GPS data tracking, and social network analysis, among others.

Finally, you’ll explore statistical learning. With SciPy, you’ll learn and apply the basics of linear and logistic regression, and learn how to use random forests to analyze a movie dataset.

How You’ll Learn

The course is 5 weeks long and you are expected to spend 2 to 4 hours each week on it. Video lectures and project materials are provided as resources, and in each week you’ll be given one or more homework assignments to complete.

There'll be final project that you’ll have to complete as a verified learner.

Institution	Harvard University
Provider	edX
Instructor	Jukka-Pekka "JP" Onnela
Level	Intermediate
Workload	20 hours total
Enrollments	308K
Certificate	Paid

Fun Facts

The course instructor, Jukka-Pekka "JP" Onnela, was awarded the NIH Director's New Innovator Award in 2013 for his work in digital phenotyping.
It may not come as a surprise then that he’s Associate Professor of Biostatistics at Harvard University.

If you're interested in this course, you can find more information about the course and how to enroll here.

10. Automate the Boring Stuff with Python Programming (Udemy)

Excerpt from the book Automate the Boring Stuff with Python

Last but certainly not to be overlooked is Automate the Boring Stuff with Python Programming, taught by Al Sweigart on Udemy. This course is based on the book with the same name, Automate the Boring Stuff with Python, which is freely available to read online.

This course is fairly comprehensive and introduces you to some topics other introductory courses normally don't offer, like regular expressions, web scraping, and GUI automation. Plus, as you might've guessed, this course is very hands-on and project-driven.

What You’ll Learn

You’ll begin by installing Python on your machine and get familiar with the IDLE, the default programming environment that comes bundled with Python.

You’ll learn about control flow through the visual of charts, giving you a good understanding of concepts like conditional statements, loops, and iterations. You’ll create your own functions and learn about variable scoping in Python.

You’ll also learn how to handle errors with the “try-except” blocks before cementing your understanding by building a guess-the-number game.

Of course, you’ll explore data structures like lists, dictionaries, and strings, and how to manipulate them.

Using the command line to run Python programs, you’ll discover how to automate stuff on your computer: yep, the course title is accurate! To do so, you’ll study regular expressions, how to navigate directories, and how to read or write files.

The course explores automating tasks such as web scraping, reading and editing Excel, Word, or PDF documents, sending and checking emails, controlling your mouse and keyboard using Python, and implementing image recognition scripts.

How You’ll Learn

The course is split up into 16 sections with 51 lectures. In total, it has around 9 hour and 30 minutes of lectures.

There are 95 downloadable resources, including lectures and other course material.

Provider	Udemy
Instructor	Al Sweigart
Level	Beginner
Workload	10 hours total
Enrollments	1M
Rating	4.6 / 5.0 (98K)
Certificate	Paid

Fun Facts

The creator of the course occasionally gives out Udemy coupons to his course for free on Reddit.
If you have completed the course or book and want to move on to more advanced Python stuff, you can check out the author’s new book, Beyond the Basic Stuff with Python, which is also free online.

If you're interested in this course, you can find more information about the course and how to enroll here.

Online Coding Classes – For Beginners

Jessica Wilkins — Mon, 21 Feb 2022 19:24:05 +0000

Learning how to code can help you start a great career as a software developer. There are many free courses you can take to cultivate the skills need to become a developer.

In this article, I'm going to show you 152 beginner friendly courses where you can learn computer science and programming for free.

The freeCodeCamp courses are completely free and some of them include a free certification that you can add to your LinkedIn or résumé.

Note that some of the non-freeCodeCamp courses I've listed here (such as the university courses) are free to audit, but do require you to pay a fee if you want a certificate.

Here is the complete list of free courses, arranged by topic. Once you find a course that interests you, click that link and it will jump you down to a more detailed description of that course.

Computer Science Courses (16)

Introduction to Programming and Computer Science (freeCodeCamp)
Data Structures - Computer Science Course for Beginners (freeCodeCamp)
CS50's Introduction to Computer Science (Harvard University)
Introduction to Computer Science and Programming Using Python (MIT)
Introduction to Algorithms (MIT)
Big O Notation (freeCodeCamp)
Graph Algorithms for Technical Interviews (freeCodeCamp)
Recursion in Programming (freeCodeCamp)
Data Structures - Full Course Using C and C++ (freeCodeCamp)
Dynamic Programming - Learn to Solve Algorithmic Problems & Coding Challenges (freeCodeCamp)
Algorithms and Data Structures (freeCodeCamp)
Data Structures and Algorithms in Python - Full Course for Beginners (freeCodeCamp)
An Introduction to Interactive Programming in Python Part 1 (Rice University)
Learn to Program: The Fundamentals (University of Toronto)
Code Yourself! An Introduction to Programming (The University of Edinburgh)
Learn to Program: Crafting Quality Code (University of Toronto)

Git and Github Courses (4)

Git and GitHub for Beginners - Crash Course (freeCodeCamp)
Git & GitHub Crash Course For Beginners (Brad Traversy)
Git Tutorial for Beginners: Learn Git in 1 Hour (Programming with Mosh)
Git Tutorial for Beginners - Git & GitHub Fundamentals In Depth (Tech With Tim)

HTML Courses (8)

Basic HTML and HTML5 (freeCodeCamp)
HTML Full Course - Build Your Own Website (freeCodeCamp)
Introduction to HTML5 (University of Michigan)
HTML Tutorial for Beginners: HTML Crash Course 2021 (Programming with Mosh)
HTML Crash Course For Absolute Beginners (Traversy Media)
Learn HTML (Codecademy)
HTML For Beginners The Easy Way (html.com)
HTML Crash Course for Beginners - Website Tutorial (freeCodeCamp)

CSS Courses (15)

Responsive Web Design (freeCodeCamp)
Intro to HTML and CSS (Udacity)
HTML and CSS Tutorial (MarkSheet)
CSS Tutorial - Zero to Hero (freeCodeCamp)
CSS Crash Course For Absolute Beginners (Traversy Media)
Introduction to CSS3 (University of Michigan)
CSS Basics (W3C)
Sass Tutorial for Beginners - CSS With Superpowers (freeCodeCamp)
Bootstrap 5 tutorial - crash course for beginners in 1.5H (Keep Coding YouTube channel)
Learn CSS Media Queries by Building 3 Projects (freeCodeCamp)
CSS Flexbox Crash Course (freeCodeCamp)
Learn Bootstrap 5 and SASS by Building a Portfolio Website (freeCodeCamp)
Tailwind CSS Crash Course (Traversy Media)
HTML and CSS ( The Odin Project)
Bootstrap CSS Framework - Full Course for Beginners (freeCodeCamp)

UI/UX (12)

Foundations of User Experience (UX) Design (Google)
Start the UX Design Process: Empathize, Define, and Ideate (Google)
Build Wireframes and Low-Fidelity Prototypes (Google)
Conduct UX Research and Test Early Concepts (Google)
Create High-Fidelity Designs and Prototypes in Figma (Google)
Responsive Web Design in Adobe XD (Google)
Free Adobe XD Tutorial: User Experience Design Course with Adobe XD Course (Bring Your Own Laptop Youtube channel)
The 2019 UI Design Crash Course for Beginners (DesignCourse)
Figma Tutorial - A Free UI Design/Prototyping Tool (DesignCourse)
UXpin: Free UX Ebooks (uxpin.com)
Figma Course - Web Design Tutorial for Beginners (freeCodeCamp)
Figma Tutorial for UI Design - Course for Beginners (freeCodeCamp)

JavaScript Courses (13)

JavaScript Algorithms and Data Structures (freeCodeCamp)
Learn JavaScript - Full Course for Beginners (freeCodeCamp)
Full Stack JavaScript (The Odin Project)
The Modern JavaScript Tutorial (javascript.info)
JavaScript Tutorial (javascripttutorial.net)
LearnJS (learn-js.org)
JavaScript (SoloLearn)
JavaScript Programming (freeCodeCamp)
JavaScript Tutorial for Beginners: Learn JavaScript in 1 Hour (Programming with Mosh)
TypeScript Course for Beginners 2021 - Learn TypeScript from Scratch! (Academind)
Backend Development and API's (freeCodeCamp)
Node.js and Express.js - Full Course (freeCodeCamp)
Node.js Tutorial for Beginners: Learn Node in 1 Hour (Programming with Mosh)

JavaScript Frameworks and Libraries (14)

freeCodeCamp React Course (freeCodeCamp)
React Course - Beginner's Tutorial for React JavaScript Library [2022] (freeCodeCamp)
Scrimba React course (Scrimba)
React JS - React Tutorial for Beginners (Programming with Mosh)
React JS Crash Course 2021 (Brad Traversy)
freeCodeCamp Redux Course (freeCodeCamp)
Redux For Beginners | React Redux Tutorial (Dev Ed)
Thinkster Angular Tutorial (Thinkster)
Angular Crash Course (Brad Traversy)
Learn Angular - Full Tutorial Course (freeCodeCamp)
Vue.js Course for Beginners [2021 Tutorial] (freeCodeCamp)
Vue JS Crash Course 2021 (Brad Traversy)
Data Visualization with D3, JavaScript, React - Full Course [2021] (freeCodeCamp)
Next.js for Beginners - Full Course (freeCodeCamp)

Python Courses (22)

Programming for Everybody (Getting Started with Python) (University of Michigan)
Python Data Structures (University of Michigan)
Using Python to Access Web Data (University of Michigan)
Using Databases with Python (University of Michigan)
An Introduction to Interactive Programming in Python (Part 1) (Rice University)
An Introduction to Interactive Programming in Python (Part 2) (Rice University)
Scientific Computing with Python (freeCodeCamp)
Python Django Web Framework - Full Course for Beginners (freeCodeCamp)
Learn Python - Full Course for Beginners (freeCodeCamp)
The Python Handbook (Flavio Copes)
Python Tutorials for Absolute Beginners (CS Dojo)
Studytonight (studytonight.com/python/)
Python Core (SoloLearn)
Python Basics with Sam (freeCodeCamp)
Python Beginner Tutorials (Pythonspot)
Python Tutorial (PythonForBeginners)
Automate the Boring Stuff with Python (Al Sweigart)
Python Crash Course For Beginners (Traversy Media)
Python Tutorial - Python for Beginners (Programming with Mosh)
PySpark Tutorial (freeCodeCamp)
Python Backend Web Development Course (with Django) (freeCodeCamp)
Flask Course - Python Web Application Development (freeCodeCamp)

Mobile App Development Courses (5)

Android Development for Beginners - Full Course (freeCodeCamp)
React Native Tutorial for Beginners - Build a React Native App [2020] (Programming with Mosh)
Kotlin Course - Tutorial for Beginners (freeCodeCamp)
Swift Programming Tutorial for Beginners (Code with Chris)
Learn iOS Development by Building a Netflix Clone (freeCodeCamp)

Game Development Courses (5)

CS50's Introduction to Game Development (Harvard)
Learn Unity - Beginner's Game Development Tutorial (freeCodeCamp)
Create A 2.5D Platformer Game With Unreal Engine (freeCodeCamp)
Pygame Tutorial for Beginners - Python Game Development Course (freeCodeCamp)
Godot Game Engine Tutorial - Make a 2D Platformer Game (freeCodeCamp)

C, C++, C# Courses (7)

C Programming Tutorial for Beginners (freeCodeCamp)
C++ Tutorial for Beginners - Full Course (freeCodeCamp)
C# Tutorial - Full Course for Beginners (freeCodeCamp)
C Course (SoloLearn)
C++ Course (SoloLearn)
C# Course (SoloLearn)
Learn C++ Programming for Beginners – Free 31-Hour Course (freeCodeCamp)

Java Courses (12)

Java Programming: Solving Problems with Software (Coursera)
Java Programming: Arrays, Lists, and Structured Data (Coursera)
Java Programming: Principles of Software Design (Coursera)
Java Programming Basics (Udacity)
Java Programming (Test Automation University)
Intro to Java Programming Course for Absolute Beginners (freeCodeCamp)
Learn Functional Programming in Java (freeCodeCamp)
Java Virtual Machine Architecture Explained for Beginners (freeCodeCamp)
Java Tutorial for Beginners [2020] (Programming with Mosh)
Spring Boot Tutorial for Beginners (freeCodeCamp)
Java Testing - JUnit 5 Crash Course (freeCodeCamp)
Java Course (SoloLearn)

PHP Courses (4)

PHP Programming Language Tutorial - Full Course (freeCodeCamp)
PHP For Absolute Beginners (Traversy Media)
Use PHP to Create an MVC Framework - Full Course (freeCodeCamp)
PHP Tutorial for Beginners - Full Course (Envato Tuts)

Ruby on Rails Courses (2)

Learn Ruby on Rails - Full Course (freeCodeCamp)
Full Stack Ruby on Rails (The Odin project)

Databases (13)

Relational Database Curriculum (freeCodeCamp)
SQL Tutorial - Full Database Course for Beginners (freeCodeCamp)
Learn SQL In 60 Minutes (Web Dev Simplified)
SQL For Beginners Tutorial (Amigoscode)
MySQL Database - Full Course (freeCodeCamp)
MySQL Tutorial for Beginners - Full Course (Programming with Mosh)
MySQL Crash Course | Learn SQL (Traversy Media)
SQL for Data Science (UC Davis)
Database Systems - Cornell University Course (SQL, NoSQL, Large-Scale Data Analysis) (freeCodeCamp)
SQLite Databases With Python (freeCodeCamp)
Learn PostgreSQL Tutorial - Full Course for Beginners (freeCodeCamp)
MongoDB Crash Course (Traversy Media)
NoSQL Database Tutorial – Full Course for Beginners (freeCodeCamp)

Computer Science Courses

Introduction to Programming and Computer Science

In this freeCodeCamp YouTube course, you will learn about arrays, loops, functions, recursion, conditions, and data structures.

Data Structures - Computer Science Course for Beginners

In this freeCodeCamp YouTube course, you will learn about arrays, Big O notation, linked lists, hash tables, heaps, and tries.

CS50's Introduction to Computer Science

This Harvard course will teach you basic computer science concepts like algorithms and data structures through a series of problem sets and a final project.

Introduction to Computer Science and Programming Using Python

This MIT course will teach you basic computer science concepts like algorithms, data structures, testing, and debugging through a series of problem sets.

Introduction to Algorithms

In this MIT course, you will learn about dynamic programming, hashing, graphs, trees and sorting algorithms. You will also learn how to measure the performance of algorithms and data structures.

Big O Notation

In this freeCodeCamp YouTube course, you will learn about Big O notation and how to apply it to recursive solutions, iterative solutions, and sorting algorithms.

Graph Algorithms for Technical Interviews

In this freeCodeCamp YouTube course, you will learn about breadth first and depth first graph traversals. You will also work on several challenges including connected components count, shortest path, and island count.

Recursion in Programming

In this freeCodeCamp YouTube course, you will learn about recursion, divide & conquer algorithms, graphs trees, linked lists and more.

Data Structures - Full Course Using C and C++

In this freeCodeCamp YouTube course, you will learn about graphs, trees, linked lists, stacks and queues.

Dynamic Programming - Learn to Solve Algorithmic Problems & Coding Challenges

In this freeCodeCamp YouTube course, you will learn how to solve several challenges using dynamic programming including fib tabulation, canSum memoization, and canConstruct tabulation.

Algorithm and Data Structures

In this freeCodeCamp YouTube course, you will learn about arrays, linked lists, and sorting and searching algorithms.

Data Structures and Algorithms in Python - Full Course for Beginners

In this freeCodeCamp YouTube course, you will learn common data structures like linked lists, stacks, queues and common algorithms in Python.

An Introduction to Interactive Programming in Python Part 1 - Rice University

In this Coursera Rice University course, you will learn about the basic fundamentals behind programming including arrays, loops, functions, recursion, conditions, and data structures.

Learn to Program: The Fundamentals

In this Coursera course, you will learn the basics of programming including strings, loops, functions, tuples, and more using the Python language.

Code Yourself! An Introduction to Programming

In this Coursera course, you will learn the fundamentals of programming, algorithms and data structures by using the Scratch platform.

Learn to Program: Crafting Quality Code

In this Coursera course, you will learn about popular algorithms like Bubble sort and Binary search and you will also learn about unit testing.

Git and Github Courses

Git and GitHub for Beginners - Crash Course

In this freeCodeCamp YouTube course, you will learn about GitHub, version control, SSH keys, and common Git commands.

Git & GitHub Crash Course For Beginners

In this Brad Traversy course, you will learn about version control and popular Git commands.

Git Tutorial for Beginners: Learn Git in 1 Hour

In this Programming with Mosh course, you will learn about Git and basic commands.

Git Tutorial for Beginners - Git & GitHub Fundamentals In Depth

In this Tech with Tim course, you will learn about staging, branches, pulls and more.

HTML Courses

Basic HTML and HTML5

This freeCodeCamp course will teach you basic HTML5 elements through 28 coding exercises that you can do in the freeCodeCamp online editor (part of the free Responsive Web Design Certification).

HTML Full Course - Build a Website Tutorial

In this freeCodeCamp YouTube course, you will learn about basic HTML tags, how to use a text editor, and how to format your web page.

Introduction to HTML5

This University of Michigan course will cover the history of HTML, the Document Object Model, HTML5 tags, and accessibility.

HTML Tutorial for Beginners: HTML Crash Course 2021

Programming with Mosh will teach you the basics of HTML, how the web works, and how to use the browser developer tools.

HTML Crash Course For Absolute Beginners

This Brad Traversy course will cover the most popular HTML tags and semantic tags.

Learn HTML

In this Codecademy course, you will learn about basic HTML tags, forms, tables, and semantic tags.

HTML For Beginners The Easy Way

This HTML tutorial will cover the history of HTML, popular HTML tags, attributes, and code editors.

HTML Crash Course for Beginners - Website Tutorial

In this freeCodeCamp YouTube course, you will learn about headings, images, lists, footers, links, and more.

CSS Courses

Responsive Web Design

In this freeCodeCamp course, you will learn the basics of CSS, applied visual design, applied accessibility, responsive web design principles, CSS Flexbox, and CSS Grid. (Free Certification)

Intro to HTML and CSS

In this Udacity course, you will learn the basics of HTML and CSS.

HTML and CSS Tutorial

In this MarkSheet tutorial, you will learn about CSS text, the box model, positioning, pseudo classes, animations, and Sass.

CSS Tutorial - Zero to Hero

In this freeCodeCamp YouTube tutorial, you will learn about CSS basics, positioning, pseudo classes, and animations.

CSS Crash Course For Absolute Beginners

In this Brad Traversy YouTube course, you will learn the basics of CSS.

Introduction to CSS3

In this University of Michigan course, you will learn about CSS basics, the box model, positioning, pseudo classes, and animations.

CSS Basics

In this W3C course, you will learn about CSS selectors, layout, positioning, and accessibility.

Sass Tutorial for Beginners – CSS With Superpowers

In this freeCodeCamp YouTube course, you will learn about Sass syntax, mixins, variables, nesting, and partials.

Bootstrap 5 tutorial – crash course for beginners in 1.5H

In this Keep coding YouTube course, you will learn about Bootstrap 5 tables, buttons, cards, images, and forms.

Learn CSS Media Queries by Building 3 Projects - Full Course

In this freeCodeCamp YouTube course, you will learn how to create responsive layouts for mobile, tablet and desktop sizes by building 3 projects.

CSS Flexbox Crash Course

In this freeCodeCamp YouTube course, you will learn how to create responsive layouts in websites using Flexbox.

Learn Bootstrap 5 and SASS by Building a Portfolio Website

In this freeCodeCamp YouTube course, you will learn how to use Bootstrap and Sass.

Tailwind CSS Crash Course

In this Brad Traversy YouTube course, you will learn how to setup Tailwind CSS and work with utility classes.

HTML and CSS

In this Odin Project course, you will learn about HTML forms, HTML tables, CSS Flexbox, CSS animations, and more.

Bootstrap CSS Framework - Full Course for Beginners

In this freeCodeCamp YouTube course, you will learn about the basics of Bootstrap 5 and how to create designs with a mobile first approach.

UI/UX Courses

Foundations of User Experience (UX) Design

In this Google course, you will learn about the basics behind good UX design and accessibility.

Start the UX Design Process: Empathize, Define, and Ideate

In this Google course, you will learn about UX research and Wireframing.

Build Wireframes and Low-Fidelity Prototypes

In this Google course, you will learn about building wireframes, prototypes, and storyboards.

Conduct UX Research and Test Early Concepts

In this Google course, you will learn how to create a usability study.

Create High-Fidelity Designs and Prototypes in Figma

In this Google course, you will learn how to create good design mockups with Figma.

Responsive Web Design in Adobe XD

In this Google course, you will learn how to use Adobe XD and create responsive designs.

Free Adobe XD Tutorial: User Experience Design Course with Adobe XD Course

In this YouTube course, you will learn about the basics of UI/UX design and wireframing.

The 2019 UI Design Crash Course for Beginners

In this YouTube course, you will learn about design fundamentals and Adobe XD.

Figma Tutorial – A Free UI Design/Prototyping Tool

In this YouTube course, you will how to use the Figma design tool.

UXpin: Free UX Ebooks

UXpin is a resource that offers a variety of ebooks on mobile and web wireframing, usability testing, mockups, and more.

Figma Course - Web Design Tutorial for Beginners

In this freeCodeCamp YouTube course, you will learn the basics of how to use the Figma design tool for both mobile and desktop design.

Figma Tutorial for UI Design - Course for Beginners

In this freeCodeCamp YouTube course, you will learn about layouts, colors and design principles with Figma.

JavaScript Courses

JavaScript Algorithms and Data Structures

In this freeCodeCamp course, you will learn about basic JavaScript, ES6, regular expressions, basic data structures, Object Oriented Programming, and functional programming. (Free Certification)

Learn JavaScript – Full Course for Beginners

In this freeCodeCamp YouTube course, you will learn about conditions, loops, functions, objects, arrays, and ES6.

Full stack JavaScript

This Odin Project course will teach you HTML, CSS, JavaScript, and NodeJS through a series of lessons and projects.

The Modern JavaScript Tutorial

In this tutorial, you will learn about JavaScript basics, error handling, promises, Async/await, and the DOM.

JavaScript Tutorial

In this tutorial, you will learn JavaScript fundamentals, ES6, BOM, the DOM, and web APIs.

LearnJS

In this tutorial, you will learn about JavaScript basics, Object-Oriented Programming, inheritance, and data structures.

JavaScript

In this SoloLearn course, you will learn about conditions, loops, functions, objects, arrays, the DOM, and events.

JavaScript Programming

In this freeCodeCamp YouTube course, you will learn about the basics of JavaScript and build a black jack game and Google Chrome extension.

JavaScript Tutorial for Beginners: Learn JavaScript in 1 Hour

In this Programming with Mosh course, you will learn about JavaScript basics like objects, arrays, and functions.

TypeScript Course for Beginners 2021 – Learn TypeScript from Scratch!

In this Academind course, you will learn about array types, object types, tuples, function types, and callbacks.

Backend Development and API's

In this freeCodeCamp course, you will learn the basics of Node.js, NPM, Express, and MongoDB. (Free Certification)

Node.js and Express.js – Full Course

In this freeCodeCamp YouTube course, you will learn about NPM commands, different modules, async patterns, events, streams, and HTTP basics.

Node.js Tutorial for Beginners: Learn Node in 1 Hour

In this Programming with Mosh course, you will learn about different modules like the path module, OS module, and the file system module and NPM commands.

JavaScript Frameworks and Libraries

freeCodeCamp React Course

In this freeCodeCamp course, you will learn about JSX, functional components, class components, state, and props. (Part of the free Front End Libraries Certification)

React Course - Beginner's Tutorial for React JavaScript Library [2022]

In this freeCodeCamp YouTube course, you will learn about JSX, hooks, state, props, and more. You will also build several projects including an Airbnb clone and meme generator.

Scrimba React course

In this Scrimba course, you will learn about JSX, reusable components, state, lifecycle methods, and hooks.

React JS – React Tutorial for Beginners

In this Programming with Mosh course, you will learn about props, state, hooks, debugging React apps, and handling events.

React JS Crash Course 2021

In this Brad Traversy course, you will learn about JSX, props, state, hooks, React icons, and conditional rendering.

freeCodeCamp Redux Course

In this freeCodeCamp course, you will learn about actions, reducers, and stores. (Part of free Front End Libraries Certification)

Redux For Beginners | React Redux Tutorial

In this Dev Ed tutorial, you will learn about actions, reducers, stores, combineReducers, and Redux DevTools.

Thinkster Angular Tutorial

In this Thinkster tutorial, you will learn about lifecycle hooks, styled components, NgModel, and Angular directives.

Angular Crash Course

In this Brad Traversy course, you will learn about components, services, and modules.

Learn Angular – Full Tutorial Course

In this freeCodeCamp YouTube course, you will learn about interpolation and expressions, lifecycle hooks, components, routing, and directives.

Vue.js Course for Beginners [2021 Tutorial]

In this freeCodeCamp YouTube course, you will learn about directives, data-binding, Vue devtools, props and slots, and more.

Vue JS Crash Course 2021

In this Brad Traversy course, you will learn the basics of Vue.js by building a Random User Generator and Task Tracker.

Data Visualization with D3, JavaScript, React – Full Course [2021]

In part one and part two of this D3 course, you will learn about line charts, scatter plots, bar charts, and choropleth maps.

Next.js for Beginners - Full Course

In this freeCodeCamp YouTube course, you will learn how to build a recipe app with Next.js, Sanity.io, and Vercel. This course will cover dynamic routing, static assets, serverless functions, and more.

Python Courses

Programming for Everybody (Getting Started with Python)

In this University of Michigan course, you will learn about the basics of programming like functions, loops, conditions, and variables.

Python Data Structures

In this University of Michigan course, you will learn about tuples, dictionaries, lists, and strings.

Using Python to Access Web Data

In this University of Michigan course, you will learn about XML, APIs, regular expressions, and JSON.

Using Databases with Python

In this University of Michigan course, you will learn about relational SQL, CRUD (Create, Read, Update, and Delete) applications, and Object-Oriented patterns.

An Introduction to Interactive Programming in Python (Part 1)

This Rice University course will teach you the basics of programming like functions, loops, conditions and variables.

An Introduction to Interactive Programming in Python (Part 2)

In this Rice University course, you will learn about tuples, dictionaries, lists and strings.

Scientific Computing with Python

In this freeCodeCamp course, you will learn the basics of Python 3 while building five projects. (Free Certification)

Python Django Web Framework – Full Course for Beginners

In this freeCodeCamp YouTube course, you will learn about Django templates, Django model forms, and class-based views.

Learn Python - Full Course for Beginners

In this freeCodeCamp YouTube Course, you will learn programming basics such as lists, conditionals, strings, tuples, functions, classes and more.

You will also build several small projects like a basic calculator, mad libs game, a translator app, and a guessing game.

The Python Handbook

In this Flavio Copes article, you will learn about strings, lists, tuples, recursion, and more.

You will also learn how to install 3rd party packages and how to work with virtual environments.

Python Tutorials for Absolute Beginners by CS Dojo

In this series of Beginner Python YouTube videos by CS Dojo, you will learn about dictionaries, loops, functions, objects and more.

You will also learn how to build a Twitter bot using Python.

Studytonight

In Studytonight, you will learn about Python basics, error handling, OOP, file handling, complex data types, Multithreading and more.

Once you have learned the basics, you can move onto their other modules which include the NumPy library, Matplotlib, Tkinter, Network Programming in Python, and Web Scraping using Beautiful Soup.

Python Core

In SoloLearn's Python Course, you will learn about strings, variables, OOP, functional programming and more. There are plenty of quizzes, challenges, and projects that you can build along the way.

In order to get started, you will need to create a free account.

Python Basics with Sam (freeCodeCamp)

In this Sam Focht YouTube Series, you will learn about loops, functions, strings, recursion and more.

You will also build several projects including a guessing game, shopping list, a board game, and a random password generator.

Python Beginner Tutorials

In this series of Pythonspot beginner tutorials, you will learn about data types, tuples, objects, classes, dictionaries and more. You will also learn about advanced concepts like recursion, lambda, and threading.

Once you cover the basics, you can move onto machine learning, databases, and GUI's.

Python Tutorial

In this PythonForBeginners tutorial, you will learn about functions, loops, lists, conditionals, error handling and more.

Once you learn the basics, you can explore the other modules on the site including Web Scraping with BeautifulSoup and Using the YouTube API in Python.

Automate the Boring Stuff with Python

In the Automate the Boring Stuff with Python online book, you will learn about dictionaries, strings, debugging, regular expressions and more.

If you prefer a video format, then you can go through the YouTube series that Al Sweigart put together.

Python Crash Course for Beginners

In this Brad Traversy YouTube course, you will learn about lists, tuples, dictionaries, functions, classes and more. Brad will also show you how to work with files and JSON data.

Python Tutorial - Python for Beginners

In this Programming with Mosh YouTube course, you will learn programming basics like variables, loops, strings, tuples, functions, classes and more.

You will also build three projects: one on automation, one on machine learning, and one on building a website with Django.

For additional practice, you can go through Mosh's 53 Python Exercises for Beginners.

PySpark Tutorial

In this freeCodeCamp YouTube course, you will learn about PySpark dataframes, PySpark GroupBy and aggregate functions, databricks, and more.

Python Backend Web Development Course (with Django)

In this freeCodeCamp YouTube course, you will learn about the basics of Python and Django. You will also build a blog, weather app, and a Realtime Chat App.

Flask Course - Python Web Application Development

In this freeCodeCamp YouTube course, you will learn about Flask forms, templates, validations and more by building your own e-commerce website.

Mobile App Development Courses

Android Development for Beginners – Full Course

In part 1 and part 2 of this freeCodeCamp YouTube course, you will learn how to build an Android application using Java.

React Native Tutorial for Beginners – Build a React Native App [2020]

In this Programming with Mosh course, you will learn how to build an iOS and Android app using React Native.

Kotlin Course – Tutorial for Beginners

In this freeCodeCamp YouTube course, you will learn about basic Kotlin functions, class methods, higher-order functions, and the Kotlin standard library.

Swift Programming Tutorial for Beginners

In this Code with Chris course, you will learn about the basics of Swift like variables, constants, data types, functions, and classes.

Learn iOS Development by Building a Netflix Clone

In this freeCodeCamp YouTube course, you will learn about the basics of using Swift by building a Netflix clone.

Game Development Courses

CS50's Introduction to Game Development

In this Harvard course, you will learn how to work with popular game engines like LÖVE 2D and Unity. You will also work with the Lua and C# programming languages.

Learn Unity – Beginner's Game Development Tutorial

In this freeCodeCamp YouTube course, you will learn how to get started building games using the Unity game engine.

Create A 2.5D Platformer Game With Unreal Engine

In this freeCodeCamp YouTube course, you will learn how to work with the Unreal game engine and C++ by building a platformer game.

Godot Game Engine Tutorial - Make a 2D Platformer Game

In this freeCodeCamp YouTube course, you will learn how to use the Godot game engine while building a platformer gamer.

Pygame Tutorial for Beginners - Python Game Development Course

In this freeCodeCamp YouTube course, you will learn how to use PyGame by building a space invaders game.

C, C++, C# Courses

C Programming Tutorial for Beginners

In this freeCodeCamp YouTube course, you will learn about pointers, memory, functions, arrays and more.

C++ Tutorial for Beginners - Full Course

In this freeCodeCamp YouTube course, you will learn about pointers, inheritance, arrays, conditionals and more.

C# Tutorial - Full Course for Beginners

In this freeCodeCamp YouTube course, you will learn about conditionals, strings, objects, arrays, and more.

C Course

In this SoloLearn course, you will learn about data types, arrays, pointers, loops, strings, unions, memory management and more.

C++ Course

In this SoloLearn course, you will learn about pointers, conditionals, functions, classes, objects, polymorphism and more.

C# Course

In this SoloLearn course, you will learn about arrays, strings, structs, enums and more.

Learn C++ Programming for Beginners – Free 31-Hour Course

In this freeCodeCamp YouTube course, you will about programming fundamentals like flow control, loops, function, arrays, pointers and more.

Java Courses

Java Programming: Solving Problems with Software

In this Coursera course, you will learn about classes, conditionals, loops, functions and more. You will also learn how to work with CSV files in Java and build a mini project.

Java Programming: Arrays, Lists, and Structured Data

In this Coursera course, you will learn about arrays, cryptography, HashMaps, and more. You will also build a mini project about the Vigenère cipher.

Java Programming: Principles of Software Design

In this Coursera course, you will learn about different sorting algorithms, and the basics of predictive text.

Java Programming Basics

In this Udacity course, you will learn about arrays, objects, classes, loops, debugging, and more.

Once you finish the beginner course, then you can take this intermediate Object Oriented Programming course.

Java Programming

In this Test Automation University course, you will learn about classes, loops, switch statements, conditionals, arrays, strings, abstraction and more.

Intro to Java Programming Course for Absolute Beginners

In this freeCodeCamp YouTube course, you will learn about arrays, objects, classes, loops, debugging, and more.

Learn Functional Programming in Java

In this freeCodeCamp YouTube course, you will learn about the properties of functional programming, callbacks, functional interfaces, combinator pattern, lambdas, and more.

Java Virtual Machine Architecture Explained for Beginners

In this freeCodeCamp article, you will learn about the Java Virtual Machine as well as the architecture behind it.

Java Tutorial for Beginners [2020]

In this Programming with Mosh YouTube course, you will learn about strings, arrays, conditionals, loops and more. You will also build a mortgage calculator.

Spring Boot Tutorial for Beginners (Java Framework)

In this freeCodeCamp YouTube course, you will learn the basics of how to use this popular Java framework.

Java Testing - JUnit 5 Crash Course

In this freeCodeCamp YouTube course, you will learn about JUnit Architecture, conditional executions, assumptions and more.

Java Course

In this SoloLearn course, you will learn about arrays, objects, classes, loops, and more.

PHP Courses

PHP Programming Language Tutorial - Full Course

In this freeCodeCamp YouTube course, you will learn about loops, functions, classes, objects, and more.

PHP For Absolute Beginners

In this Brad Traversy YouTube tutorial, you will learn about objects, loops, arrays and more. You will also build a basic CRUD (create, read, update, delete) application.

Use PHP to Create an MVC Framework - Full Course

In this freeCodeCamp YouTube course, you will learn how to work with file systems, custom routing, third party packages using composer, and more.

PHP Tutorial for Beginners - Full Course

In this Envato Tuts course, you will learn the basics of PHP like functions, variables arrays and more. You will also learn how to connect a MySQL database to your PHP application.

Ruby on Rails Courses

Learn Ruby on Rails - Full Course

In this freeCodeCamp YouTube course, you will learn how to make a Friends List App using Ruby on Rails.

Full Stack Ruby on Rails

In this Odin project curriculum, you will learn about Ruby, relational databases, Ruby on Rails, and more.

Databases

Relational Database freeCodeCamp Curriculum

In September of 2021, freeCodeCamp released the beta version of their relational database curriculum. This beta version is run entirely in Visual Studio Code using Docker and a CodeRoad extension.

In this course, you will learn about Git, GitHub, Bash, Nano, SQL, PostgreSQL and more. This is an entirely project-based learning curriculum.

Some of the projects that you will build in the course include a Mario database, World database, Celestial Bodies database, and a Bike rental shop.

To learn more about it, you can read through this article by Tom Mondloch who created the course.

SQL Tutorial - Full Database Course for Beginners

In this freeCodeCamp YouTube course, Mike Dane will teach you the basics of SQL. You will learn about creating tables, inserting data, wildcards, unions, joins and more.

In this course, you will learn how to install MySQL on your Mac or Windows computer. You will also practice your SQL skills by building a company database and an ER diagram.

If you like this course by Mike Dane, then please check out their YouTube channel for more free courses.

Learn SQL In 60 Minutes

In this Web Dev Simplified YouTube course, Kyle will teach you the basics of getting started with SQL. You will learn about creating tables, inserting data into tables, primary keys, foreign keys, aggregate functions, and more.

This is a great course to take as a quick introduction to learning about the basics. From here you can move onto building your first few projects using SQL.

SQL For Beginners Tutorial

In this Amigoscode YouTube course, Nelson will teach you how to get setup using PostgreSQL on Mac and Windows. You will then learn the basics of SQL including creating tables, primary keys, foreign keys, aggregate functions, and more.

If you enjoy this free YouTube course by Nelson, then you can check out his other courses on his channel or take a look at his paid courses on his website.

MySQL Database - Full Course

In this freeCodeCamp YouTube course, Bharath will teach you how to install MySQL on your local machine. You will then learn how to create tables, insert data into tables, do data modeling, locks, use SQL Explain, and more.

Bharath also provides helpful resources to go along with the course including a getting started guide and GitHub repository of the MySQL scripts.

If you enjoyed this course, then you can visit other courses on their YouTube channel.

MySQL Tutorial for Beginners - Full Course

In this Programming with Mosh YouTube course, Mosh will teach you how to install MySQL on Mac or Windows. You will then learn about creating tables, inserting data into databases, joins, operators, SQL clauses, SQL operators, and more.

If you enjoy this course by Mosh, then you can visit their YouTube channel or his website for paid courses.

MySQL Crash Course | Learn SQL

In this Traversy Media YouTube course, Brad will teach you the basics of getting started with MySQL. You will learn about creating tables, inserting data into tables, altering tables, primary keys, foreign keys, aggregate functions and more.

This is a great course to take as a quick introduction to learning about the basics. From here you can move onto building your first few projects using MySQL.

Brad also includes a MySQL Cheat Sheet with this course.

SQL for Data Science

In this UC Davis course, you will learn the basics of how to use SQL in the context of Data Science. You will learn about creating tables, inserting data into tables, primary keys, foreign keys, aggregate functions, joins, subqueries, and more.

This course is free to audit on Coursera. It is also part of the Learn SQL Basics for Data Science Specialization.

If you are interested in continuing with the specialization, then I would suggest looking into the other three courses offered after this introductory course.

Database Systems - Cornell University Course (SQL, NoSQL, Large-Scale Data Analysis)

In this freeCodeCamp YouTube course, you will learn how to query database systems, index data, process queries, and more.

Here is part 2 of the course as well.

SQLite Databases With Python - Full Course

In this freeCodeCamp YouTube course, you will learn how to create tables, format results, update records, delete records and more.

Learn PostgreSQL Tutorial - Full Course for Beginners

In this freeCodeCamp YouTube course, you will learn about NULLIF, primary keys, foreign keys and more.

MongoDB Crash Course

In this Brad Traversy YouTube course, you will learn how to work with MongoDB shell, MongoDB atlas and more.

NoSQL Database Tutorial – Full Course for Beginners

In this freeCodeCamp YouTube course, you will learn about the basics of NoSQL and build two small projects.

How to Audit a Class Online – Learn from Free University Courses

freeCodeCamp — Wed, 16 Feb 2022 14:13:29 +0000

By Seth Goldin

These days, there are thousands of publicly available college courses on the web. You can audit those courses even if you're not enrolled in a program.

In our video course, Sam Crombie and I explore what auditing is and why you should consider trying it.

We discuss how to choose a topic and a course to learn about that topic, and then how to make the most of your experience. By the end, you’ll be ready to audit courses on the web and succeed in them.

This condensed accompanying article will highlight key information from our video.

Learning on the Internet

The internet, a recent addition to our educational arsenal, has revolutionized accessibility to content. It has led to the rise of auto-didacticism, or self-guided learning.

Whether you're using the internet to complement, substitute, or as a component of conventional education, you're in control. To be an autodidact is to determine the topic you study, the source you learn from, and when you learn it.

The ability to learn on your own using the internet is among the most valuable skills you can develop. There has never been a better time to pursue what you're interested in!

What does it Mean to Audit a Class?

Auditing a course means taking a course offered by an institution for no credit or grade. You might audit a course (instead of taking it for credit) because of time, financial constraints, or the difficulty of material.

Auditing usually gives you access to lecture videos, notes, projects, and/or assignments. But it lacks personalized interaction with professors, teaching assistants, lab instructors, or other students. Fortunately, online communities can act as a substitute for such traditional class support.

In other words, to 'audit' is to learn from a complete outline of a course without interaction or feedback.

Since the early days of the internet, people have been auditing university courses in many forms. One of the earliest institution-supported platforms for e-learning was MIT’s OpenCourseWare (OCW).

OCW has operated since 2002 and has posted hundreds of variations of their courses to audit. Other platforms have posted or compiled public learning materials, such as College Compendium.

“Learning on the web” also encompasses news, online encyclopedias, documentation, blogs, and forums. Choosing when/where/how to learn involves deciding between organized or personalized materials.

With a structured curriculum, you always know what you’re supposed to do next. You can be confident that someone has taken the time to arrange the order of your learning in a beneficial way.

A customizable curriculum enables you to learn from several resources in any order. Everything is according to your personal needs and preferred learning style.

Auditing courses on the web provides a cost-conscious, low-risk format for academic exploration. You keep the benefits of a structured college curriculum while retaining customizability.

Auditing a course bridges the gap between self-guided and institution-based learning.

Auditing is only one component of an ecosystem of resources on the web that exist to help people learn. Many resources complement one another, utilized by platforms and courses interchangeably. Take advantage of them!

Why Audit Courses Online?

Auditing as an educational resource has many use-cases. You may benefit academically, intellectually, or professionally while learning from computer science courses. For example:

If you're a student applying to college:

Understanding an institution’s offerings in specific departments can be very valuable. Auditing allows you to explore the type of instruction and topics offered.

With more and more college students taking advantage of e-learning, you can likely find specific course material. Auditing classes at a university you're interested in attending may inform your decision.

If you're a student enrolled in college:

Auditing courses can supplement ongoing classes. It can also cover material on niche or advanced topics your school may not offer.

This also applies to courses you're looking to take in the future at your university. We recommend consulting with your department to ensure you aren’t breaking any rules.

For students in a bootcamp/certificate program, university courses can complement your curriculum. They can give you perspective into the organization and implementation of conventional academics.

If you're a professional looking to upskill or learn something new:

Auditing is a fantastic way to pick up new skills or refresh old knowledge. Learning from online courses can differentiate and keep you competitive within your profession.

If you have a technical career, learning new languages and frameworks is a necessity. Through auditing, you'll be able to stay up-to-date with changing technologies.

Even if your situation isn’t reflected in one of these examples, auditing is for everyone. The breadth of available content means that, regardless of your background, auditing has something for you.

How to Choose the Right Course to Audit

Before diving into a new topic, consider the following:

What are you interested in?
Why are you interested in that topic?
What are you hoping to gain by learning about it?
How excited are you about spending your free time learning your chosen topic?
Did you choose the topic for independent study or is it a component of an ongoing curriculum?

Your answers will help you figure out what you want to learn and why.

If you can't find a topic you’re passionate about, consider actionable content. Your motivations should be reflected in the course you ultimately decide to audit:

Have you always wanted to learn how to build an app, a website, or a game?
Are you trying to practice and improve your skills for coding interviews?
Are you looking to expand your skills in a particular field such as data science?

After identifying your interests, acknowledging your skill level is critical. Consider how much prior exposure you have to your topic of choice. A lot of courses are inherently sorted by proficiency.

Prerequisites often contain information within the scope of your selected topic. They can help you identify your competence and where it may make sense to begin. Recognizing your goals is also essential:

Is there something specific you want to leave the course understanding?
If the course is applied, what do you to build by the end, or have the capability to build?
Are you aiming to build skills to pass an interview?

If you can identify what you’re working towards, you may be more focused and assign a higher value to your progress.

Assessing your interests, skill level, and goals will help you make this decision. Ultimately, choosing the right topic may mean a gut feeling of genuine excitement or strong motivation.

Selecting a course to learn from the thousands available can be overwhelming. Contemplate your preferred learning style and available timeframe to find a starting point.

When reviewing potential courses, evaluate:

How much time can you commit to this course?
What might alter your schedule, and how would that impact your goals?
What teaching styles have you enjoyed in the past? Do you prefer lecture-heavy or project-based courses?
What forms of content do you enjoy consuming? Written notes? Powerpoint slides? Audio/podcast? Video lecture with slides? Video lecture without slides? Reading documentation and experimenting?
Do you enjoy fast-paced “drink from a firehose” courses or deeper discussions?
Is there a particular source you’d prefer to learn from?

We encourage you to experiment before committing. Read the course description, syllabus, prerequisites, and other information covering course structure and delivery.

If you feel comfortable with proceeding, advance to the first lesson. Work through the lecture and relevant assignments as if you were a student taking the class.

Take note of how the content was delivered. Check your comprehension of any corresponding supplemental material.

Do you feel prepared to proceed with subsequent lessons? If you’re confident and excited, you’ve found the right course!

How to Make the Most of Your Audit

Let’s get the most out of your audit. Thinking about scheduling, accountability, and available resources will help you succeed.

The most difficult part of taking an online course often isn’t getting started. Rather, it's pushing forward when the work becomes more time-consuming or demanding.

Return to the earlier reasons that led you to choose a specific topic and course. What are you hoping to get out of this experience, and what schedule enables you to make the most of your learning?

If there is a time-sensitive nature to learning any material, think about the potential impact of going through the material more quickly. It may make sense to prioritize some parts of a course over others.

Educators and content creators often put a lot of thought into the organization of their courses. But that does not always mean that structure will be the perfect fit for you.

Everyone has different levels of dedication. Learning often and on a regular basis is generally a good method for success.

Auditing can be a long process. Breaking down your course into short-term goals can make your path feel less intimidating and more rewarding.

It’s impossible to “fail” a free online course with no grades, so if you’re struggling with something, take your time. Review the material and chat with other people learning online for help.

Engaging with other people learning online is one of the best ways to stay motivated. While you’re likely driven to be reading this article, everyone can do with some peer support from time to time.

Finding someone to hold you accountable is a great way to ensure you put in continuous effort. Enlist a friend to audit the class with you, or regularly inquire about your progress.

Common challenges of auditing a course

There are several common pitfalls that auditors often experience. They usually all lead to the same thing – not completing your course.

Throughout your audit, pay attention to see if you're mismanaging your time. Identify potential distractions and avoid speeding through material you’re unfamiliar with.

You can also enrich your learning through complementary resources. Educators often link to relevant material for you to peruse.

You can expand far beyond the resources provided in the course you’re currently auditing. There may be relevant public textbooks, YouTube series, and freeCodeCamp courses and articles. You can even dive into academic papers.

There are a lot of actions you can take to improve your auditing experience and make the most of your time. Use them!

Next Steps After Completing a Course

At this point, you’ve completed your hypothetical course. Before moving on, ensure you’ve fully reviewed the material.

There’s little point to auditing a course if you walk away without a strong understanding of the content. Now assess:

Have you reached your goals, or made progress on them?
Do you have all the skills you’ll need for that project you wanted to build? For an internship or position you’ve been aiming for?
Are you academically prepared to move on to another course building on this subject?

Regardless of your answers, congratulations! A successful audit demonstrates strong motivation and effort.

But there’s always more to learn. Your online education is never finished, the question is simply how to proceed in the short term.

If you’re looking to learn a specific skill-set, such as machine learning, chances are one course won’t be enough. Sequencing courses to effectively audit an unofficial “degree” can be incredibly useful.

There are many, many resources on the web where people have compiled courses. Such repositories often create pathways for becoming highly skilled through successive auditing.

In other words, you'll be following a trajectory similar to a real curriculum. Start with foundations of a topic and build on them, gradually becoming more specific.

Another aspect of auditing is the ability to mix and match courses from various sources.

You can learn one topic from MIT OCW and then the next from public Berkeley YouTube lectures. This ability to interchange your learning allows you to pick the classes that appeal the most to you.

Successive auditing from several sources can create an even more valuable learning experience.

Auditing Courses Gives You Freedom

Freedom is the central theme of online self-guided learning.

Choose your own content, based on your interests. Choose your learning format, your teacher, and the source of your class. Choose your own schedule. Choose what you learn next. It’s all up to you.

You’re now informed to make these decisions and achieve your goals through auditing.

Thank you for reading! We hope that you come away feeling prepared and excited to learn by auditing courses on the web!

If you’re unsure where to start, try searching for your interest on collegecompendium.org. We’ve curated hundreds of courses for you on all manner of popular programming areas.

For a deeper dive into everything discussed in this article and more, check out our video course here:

This article was co-authored by Samuel Crombie. Thank you to Computer Vectors by Vecteezy for the cover image.

Learn Programming – Free Software Development Courses for Beginners

Jessica Wilkins — Mon, 24 Jan 2022 16:05:46 +0000

In this article, I'm going to show you 140 beginner friendly courses where you can learn computer science and programming for free.

The freeCodeCamp courses are completely free and some of them include a free certification that you can add to your LinkedIn or résumé.

Note that some of the non-freeCodeCamp courses I've listed here (such as the university courses) are free to audit, but do require you to pay a fee if you want a certificate.

Here is the complete list of free courses, arranged by topic. Once you find a course that interests you, click that link and it will jump you down to a more detailed description of that course.

Computer Science Courses (12)

Introduction to Programming and Computer Science (freeCodeCamp)
Data Structures - Computer Science Course for Beginners (freeCodeCamp)
CS50's Introduction to Computer Science (Harvard University)
Introduction to Computer Science and Programming Using Python (MIT)
Introduction to Algorithms (MIT)
Big O Notation (freeCodeCamp)
Graph Algorithms for Technical Interviews (freeCodeCamp)
Recursion in Programming (freeCodeCamp)
Data Structures - Full Course Using C and C++ (freeCodeCamp)
Dynamic Programming - Learn to Solve Algorithmic Problems & Coding Challenges (freeCodeCamp)
Algorithms and Data Structures (freeCodeCamp)
Data Structures and Algorithms in Python - Full Course for Beginners (freeCodeCamp)

Git and Github Courses (2)

Git and GitHub for Beginners - Crash Course (freeCodeCamp)
Git & GitHub Crash Course For Beginners (Brad Traversy)

HTML Courses (8)

Basic HTML and HTML5 (freeCodeCamp)
HTML Full Course - Build Your Own Website (freeCodeCamp)
Introduction to HTML5 (University of Michigan)
HTML Tutorial for Beginners: HTML Crash Course 2021 (Programming with Mosh)
HTML Crash Course For Absolute Beginners (Traversy Media)
Learn HTML (Codecademy)
HTML For Beginners The Easy Way (html.com)
HTML Crash Course for Beginners - Website Tutorial (freeCodeCamp)

CSS Courses (15)

Responsive Web Design (freeCodeCamp)
Intro to HTML and CSS (Udacity)
HTML and CSS Tutorial (MarkSheet)
CSS Tutorial - Zero to Hero (freeCodeCamp)
CSS Crash Course For Absolute Beginners (Traversy Media)
Introduction to CSS3 (University of Michigan)
CSS Basics (W3C)
Sass Tutorial for Beginners - CSS With Superpowers (freeCodeCamp)
Bootstrap 5 tutorial - crash course for beginners in 1.5H (Keep Coding YouTube channel)
Learn CSS Media Queries by Building 3 Projects (freeCodeCamp)
CSS Flexbox Crash Course (freeCodeCamp)
Learn Bootstrap 5 and SASS by Building a Portfolio Website (freeCodeCamp)
Tailwind CSS Crash Course (Traversy Media)
HTML and CSS ( The Odin Project)
Bootstrap CSS Framework - Full Course for Beginners (freeCodeCamp)

UI/UX (12)

Foundations of User Experience (UX) Design (Google)
Start the UX Design Process: Empathize, Define, and Ideate (Google)
Build Wireframes and Low-Fidelity Prototypes (Google)
Conduct UX Research and Test Early Concepts (Google)
Create High-Fidelity Designs and Prototypes in Figma (Google)
Responsive Web Design in Adobe XD (Google)
Free Adobe XD Tutorial: User Experience Design Course with Adobe XD Course (Bring Your Own Laptop Youtube channel)
The 2019 UI Design Crash Course for Beginners (DesignCourse)
Figma Tutorial - A Free UI Design/Prototyping Tool (DesignCourse)
UXpin: Free UX Ebooks (uxpin.com)
Figma Course - Web Design Tutorial for Beginners (freeCodeCamp)
Figma Tutorial for UI Design - Course for Beginners (freeCodeCamp)

JavaScript Courses (13)

JavaScript Algorithms and Data Structures (freeCodeCamp)
Learn JavaScript - Full Course for Beginners (freeCodeCamp)
Full Stack JavaScript (The Odin Project)
The Modern JavaScript Tutorial (javascript.info)
JavaScript Tutorial (javascripttutorial.net)
LearnJS (learn-js.org)
JavaScript (SoloLearn)
JavaScript Programming (freeCodeCamp)
JavaScript Tutorial for Beginners: Learn JavaScript in 1 Hour (Programming with Mosh)
TypeScript Course for Beginners 2021 - Learn TypeScript from Scratch! (Academind)
Backend Development and API's (freeCodeCamp)
Node.js and Express.js - Full Course (freeCodeCamp)
Node.js Tutorial for Beginners: Learn Node in 1 Hour (Programming with Mosh)

JavaScript Frameworks and Libraries (14)

freeCodeCamp React Course (freeCodeCamp)
React JS Course for Beginners - 2021 Tutorial (freeCodeCamp)
Scrimba React course (Scrimba)
React JS - React Tutorial for Beginners (Programming with Mosh)
React JS Crash Course 2021 (Brad Traversy)
freeCodeCamp Redux Course (freeCodeCamp)
Redux For Beginners | React Redux Tutorial (Dev Ed)
Thinkster Angular Tutorial (Thinkster)
Angular Crash Course (Brad Traversy)
Learn Angular - Full Tutorial Course (freeCodeCamp)
Vue.js Course for Beginners [2021 Tutorial] (freeCodeCamp)
Vue JS Crash Course 2021 (Brad Traversy)
Data Visualization with D3, JavaScript, React - Full Course [2021] (freeCodeCamp)
Next.js for Beginners - Full Course (freeCodeCamp)

Python Courses (22)

Programming for Everybody (Getting Started with Python) (University of Michigan)
Python Data Structures (University of Michigan)
Using Python to Access Web Data (University of Michigan)
Using Databases with Python (University of Michigan)
An Introduction to Interactive Programming in Python (Part 1) (Rice University)
An Introduction to Interactive Programming in Python (Part 2) (Rice University)
Scientific Computing with Python (freeCodeCamp)
Python Django Web Framework - Full Course for Beginners (freeCodeCamp)
Learn Python - Full Course for Beginners (freeCodeCamp)
The Python Handbook (Flavio Copes)
Python Tutorials for Absolute Beginners (CS Dojo)
Studytonight (studytonight.com/python/)
Python Core (SoloLearn)
Python Basics with Sam (freeCodeCamp)
Python Beginner Tutorials (Pythonspot)
Python Tutorial (PythonForBeginners)
Automate the Boring Stuff with Python (Al Sweigart)
Python Crash Course For Beginners (Traversy Media)
Python Tutorial - Python for Beginners (Programming with Mosh)
PySpark Tutorial (freeCodeCamp)
Python Backend Web Development Course (with Django) (freeCodeCamp)
Flask Course - Python Web Application Development (freeCodeCamp)

Mobile App Development Courses (4)

Android Development for Beginners - Full Course (freeCodeCamp)
React Native Tutorial for Beginners - Build a React Native App [2020] (Programming with Mosh)
Kotlin Course - Tutorial for Beginners (freeCodeCamp)
Swift Programming Tutorial for Beginners (Code with Chris)

Game Development Courses (2)

CS50's Introduction to Game Development (Harvard)
Learn Unity - Beginner's Game Development Tutorial (freeCodeCamp)

C, C++, C# Courses (6)

C Programming Tutorial for Beginners (freeCodeCamp)
C++ Tutorial for Beginners - Full Course (freeCodeCamp)
C# Tutorial - Full Course for Beginners (freeCodeCamp)
C Course (SoloLearn)
C++ Course (SoloLearn)
C# Course (SoloLearn)

Java Courses (12)

Java Programming: Solving Problems with Software (Coursera)
Java Programming: Arrays, Lists, and Structured Data (Coursera)
Java Programming: Principles of Software Design (Coursera)
Java Programming Basics (Udacity)
Java Programming (Test Automation University)
Intro to Java Programming Course for Absolute Beginners (freeCodeCamp)
Learn Functional Programming in Java (freeCodeCamp)
Java Virtual Machine Architecture Explained for Beginners (freeCodeCamp)
Java Tutorial for Beginners [2020] (Programming with Mosh)
Spring Boot Tutorial for Beginners (freeCodeCamp)
Java Testing - JUnit 5 Crash Course (freeCodeCamp)
Java Course (SoloLearn)

PHP Courses (3)

PHP Programming Language Tutorial - Full Course (freeCodeCamp)
PHP For Absolute Beginners (Traversy Media)
Use PHP to Create an MVC Framework - Full Course (freeCodeCamp)

Ruby on Rails Courses (2)

Learn Ruby on Rails - Full Course (freeCodeCamp)
Full Stack Ruby on Rails (The Odin project)

Databases (13)

Relational Database Curriculum (freeCodeCamp)
SQL Tutorial - Full Database Course for Beginners (freeCodeCamp)
Learn SQL In 60 Minutes (Web Dev Simplified)
SQL For Beginners Tutorial (Amigoscode)
MySQL Database - Full Course (freeCodeCamp)
MySQL Tutorial for Beginners - Full Course (Programming with Mosh)
MySQL Crash Course | Learn SQL (Traversy Media)
SQL for Data Science (UC Davis)
Database Systems - Cornell University Course (SQL, NoSQL, Large-Scale Data Analysis) (freeCodeCamp)
SQLite Databases With Python (freeCodeCamp)
Learn PostgreSQL Tutorial - Full Course for Beginners (freeCodeCamp)
MongoDB Crash Course (Traversy Media)
NoSQL Database Tutorial – Full Course for Beginners (freeCodeCamp)

Computer Science Courses

Introduction to Programming and Computer Science

In this freeCodeCamp YouTube course, you will learn about arrays, loops, functions, recursion, conditions, and data structures.

Data Structures - Computer Science Course for Beginners

In this freeCodeCamp YouTube course, you will learn about arrays, Big O notation, linked lists, hash tables, heaps, and tries.

CS50's Introduction to Computer Science

This Harvard course will teach you basic computer science concepts like algorithms and data structures through a series of problem sets and a final project.

Introduction to Computer Science and Programming Using Python

This MIT course will teach you basic computer science concepts like algorithms, data structures, testing, and debugging through a series of problems sets.

Introduction to Algorithms

In this MIT course, you will learn about dynamic programming, hashing, graphs, trees and sorting algorithms. You will also learn how to measure the performance of algorithms and data structures.

Big O Notation

In this freeCodeCamp YouTube course, you will learn about Big O notation and how to apply it to recursive solutions, iterative solutions, and sorting algorithms.

Graph Algorithms for Technical Interviews

Recursion in Programming

In this freeCodeCamp YouTube course, you will learn about recursion, divide & conquer algorithms, graphs trees, linked lists and more.

Data Structures - Full Course Using C and C++

In this freeCodeCamp YouTube course, you will learn about graphs, trees, linked lists, stacks and queues.

Dynamic Programming - Learn to Solve Algorithmic Problems & Coding Challenges

In this freeCodeCamp YouTube course, you will learn how to solve several challenges using dynamic programming including fib tabulation, canSum memoization, and canConstruct tabulation.

Algorithm and Data Structures

In this freeCodeCamp YouTube course, you will learn about arrays, linked lists, and sorting and searching algorithms.

Data Structures and Algorithms in Python - Full Course for Beginners

In this freeCodeCamp YouTube course, you will learn common data structures like linked lists, stacks, queues and common algorithms in Python.

Git and Github Courses

Git and GitHub for Beginners - Crash Course

In this freeCodeCamp YouTube course, you will learn about GitHub, version control, SSH keys, and common Git commands.

Git & GitHub Crash Course For Beginners

In this Brad Traversy course, you will learn about version control and popular Git commands.

HTML Courses

Basic HTML and HTML5

This freeCodeCamp course will teach you basic HTML5 elements through 28 coding exercises that you can do in the freeCodeCamp online editor. (Part of the free Responsive Web Design Certification)

HTML Full Course - Build a Website Tutorial

In this freeCodeCamp YouTube course, you will learn about basic HTML tags, how to use a text editor, and how to format your web page.

Introduction to HTML5

This University of Michigan course will cover the history of HTML, the Document Object Model, HTML5 tags, and accessibility.

HTML Tutorial for Beginners: HTML Crash Course 2021

Programming with Mosh will teach you the basics of HTML, how the web works, and how to use the browser developer tools.

HTML Crash Course For Absolute Beginners

This Brad Traversy course will cover the most popular HTML tags and semantic tags.

Learn HTML

In this Codecademy course, you will learn about basic HTML tags, forms, tables, and semantic tags.

HTML For Beginners The Easy Way

This HTML tutorial will cover the history of HTML, popular HTML tags, attributes, and code editors.

HTML Crash Course for Beginners - Website Tutorial

In this freeCodeCamp YouTube course, you will learn about headings, images, lists, footers, links, and more.

CSS Courses

Responsive Web Design

In this freeCodeCamp course, you will learn the basics of CSS, applied visual design, applied accessibility, responsive web design principles, CSS Flexbox, and CSS Grid. (Free Certification)

Intro to HTML and CSS

In this Udacity course, you will learn the basics of HTML and CSS.

HTML and CSS Tutorial

In this MarkSheet tutorial, you will learn about CSS text, the box model, positioning, pseudo classes, animations, and Sass.

CSS Tutorial - Zero to Hero

In this freeCodeCamp YouTube tutorial, you will learn about CSS basics, positioning, pseudo classes, and animations.

CSS Crash Course For Absolute Beginners

In this Brad Traversy YouTube course, you will learn the basics of CSS.

Introduction to CSS3

In this University of Michigan course, you will learn about CSS basics, the box model, positioning, pseudo classes, and animations.

CSS Basics

In this W3C course, you will learn about CSS selectors, layout, positioning, and accessibility.

Sass Tutorial for Beginners – CSS With Superpowers

In this freeCodeCamp YouTube course, you will learn about Sass syntax, mixins, variables, nesting, and partials.

Bootstrap 5 tutorial – crash course for beginners in 1.5H

In this Keep coding YouTube course, you will learn about Bootstrap 5 tables, buttons, cards, images, and forms.

Learn CSS Media Queries by Building 3 Projects - Full Course

In this freeCodeCamp YouTube course, you will learn how to create responsive layouts for mobile, tablet and desktop sizes by building 3 projects.

CSS Flexbox Crash Course

In this freeCodeCamp YouTube course, you will learn how to create responsive layouts in websites using Flexbox.

Learn Bootstrap 5 and SASS by Building a Portfolio Website

In this freeCodeCamp YouTube course, you will learn how to use Bootstrap and Sass.

Tailwind CSS Crash Course

In this Brad Traversy YouTube course, you will learn how to setup Tailwind CSS and work with utility classes.

HTML and CSS

In this Odin Project course, you will learn about HTML forms, HTML tables, CSS Flexbox, CSS animations, and more.

Bootstrap CSS Framework - Full Course for Beginners

In this freeCodeCamp YouTube course, you will learn about the basics of Bootstrap 5 and how to create designs with a mobile first approach.

UI/UX Courses

Foundations of User Experience (UX) Design

In this Google course, you will learn about the basics behind good UX design and accessibility.

Start the UX Design Process: Empathize, Define, and Ideate

In this Google course, you will learn about UX research and Wireframing.

Build Wireframes and Low-Fidelity Prototypes

In this Google course, you will learn about building wireframes, prototypes, and storyboards.

Conduct UX Research and Test Early Concepts

In this Google course, you will learn how to create a usability study.

Create High-Fidelity Designs and Prototypes in Figma

In this Google course, you will learn how to create good design mockups with Figma.

Responsive Web Design in Adobe XD

In this Google course, you will learn how to use Adobe XD and create responsive designs.

Free Adobe XD Tutorial: User Experience Design Course with Adobe XD Course

In this YouTube course, you will learn about the basics of UI/UX design and wireframing.

The 2019 UI Design Crash Course for Beginners

In this YouTube course, you will learn about design fundamentals and Adobe XD.

Figma Tutorial – A Free UI Design/Prototyping Tool

In this YouTube course, you will how to use the Figma design tool.

UXpin: Free UX Ebooks

UXpin is a resource that offers a variety of ebooks on mobile and web wireframing, usability testing, mockups, and more.

Figma Course - Web Design Tutorial for Beginners

In this freeCodeCamp YouTube course, you will learn the basics of how to use the Figma design tool for both mobile and desktop design.

Figma Tutorial for UI Design - Course for Beginners

In this freeCodeCamp YouTube course, you will learn about layouts, colors and design principles with Figma.

JavaScript Courses

JavaScript Algorithms and Data Structures

In this freeCodeCamp course, you will learn about basic JavaScript, ES6, regular expressions, basic data structures, Object Oriented Programming, and functional programming. (Free Certification)

Learn JavaScript – Full Course for Beginners

In this freeCodeCamp YouTube course, you will learn about conditions, loops, functions, objects, arrays, and ES6.

Full stack JavaScript

This Odin Project course will teach you HTML, CSS, JavaScript, and NodeJS through a series of lessons and projects.

The Modern JavaScript Tutorial

In this tutorial, you will learn about JavaScript basics, error handling, promises, Async/await, and the DOM.

JavaScript Tutorial

In this tutorial, you will learn JavaScript fundamentals, ES6, BOM, the DOM, and web APIs.

LearnJS

In this tutorial, you will learn about JavaScript basics, Object-Oriented Programming, inheritance, and data structures.

JavaScript

In this SoloLearn course, you will learn about conditions, loops, functions, objects, arrays, the DOM, and events.

JavaScript Programming

In this freeCodeCamp YouTube course, you will learn about the basics of JavaScript and build a black jack game and Google Chrome extension.

JavaScript Tutorial for Beginners: Learn JavaScript in 1 Hour

In this Programming with Mosh course, you will learn about JavaScript basics like objects, arrays, and functions.

TypeScript Course for Beginners 2021 – Learn TypeScript from Scratch!

In this Academind course, you will learn about array types, object types, tuples, function types, and callbacks.

Backend Development and API's

In this freeCodeCamp course, you will learn the basics of Node.js, NPM, Express, and MongoDB. (Free Certification)

Node.js and Express.js – Full Course

In this freeCodeCamp YouTube course, you will learn about NPM commands, different modules, async patterns, events, streams, and HTTP basics.

Node.js Tutorial for Beginners: Learn Node in 1 Hour

In this Programming with Mosh course, you will learn about different modules like the path module, OS module, and the file system module and NPM commands.

JavaScript Frameworks and Libraries

freeCodeCamp React Course

In this freeCodeCamp course, you will learn about JSX, functional components, class components, state, and props. (Part of the free Front End Libraries Certification)

React Course - Beginner's Tutorial for React JavaScript Library [2022]

In this freeCodeCamp YouTube course, you will learn about JSX, hooks, state, props, and more. You will also build several projects including an Airbnb clone and meme generator.

Scrimba React course

In this Scrimba course, you will learn about JSX, reusable components, state, lifecycle methods, and hooks.

React JS – React Tutorial for Beginners

In this Programming with Mosh course, you will learn about props, state, hooks, debugging React apps, and handling events.

React JS Crash Course 2021

In this Brad Traversy course, you will learn about JSX, props, state, hooks, React icons, and conditional rendering.

freeCodeCamp Redux Course

In this freeCodeCamp course, you will learn about actions, reducers, and stores. (Part of free Front End Libraries Certification)

Redux For Beginners | React Redux Tutorial

In this Dev Ed tutorial, you will learn about actions, reducers, stores, combineReducers, and Redux DevTools.

Thinkster Angular Tutorial

In this Thinkster tutorial, you will learn about lifecycle hooks, styled components, NgModel, and Angular directives.

Angular Crash Course

In this Brad Traversy course, you will learn about components, services, and modules.

Learn Angular – Full Tutorial Course

In this freeCodeCamp YouTube course, you will learn about interpolation and expressions, lifecycle hooks, components, routing, and directives.

Vue.js Course for Beginners [2021 Tutorial]

In this freeCodeCamp YouTube course, you will learn about directives, data-binding, Vue devtools, props and slots, and more.

Vue JS Crash Course 2021

In this Brad Traversy course, you will learn the basics of Vue.js by building a Random User Generator and Task Tracker.

Data Visualization with D3, JavaScript, React – Full Course [2021]

In part one and part two of this D3 course, you will learn about line charts, scatter plots, bar charts, and choropleth maps.

Next.js for Beginners - Full Course

Python Courses

Programming for Everybody (Getting Started with Python)

In this University of Michigan course, you will learn about the basics of programming like functions, loops, conditions, and variables.

Python Data Structures

In this University of Michigan course, you will learn about tuples, dictionaries, lists, and strings.

Using Python to Access Web Data

In this University of Michigan course, you will learn about XML, APIs, regular expressions, and JSON.

Using Databases with Python

In this University of Michigan course, you will learn about relational SQL, CRUD (Create, Read, Update, and Delete) applications, and Object-Oriented patterns.

An Introduction to Interactive Programming in Python (Part 1)

This Rice University course will teach you the basics of programming like functions, loops, conditions and variables.

An Introduction to Interactive Programming in Python (Part 2)

In this Rice University course, you will learn about tuples, dictionaries, lists and strings.

Scientific Computing with Python

In this freeCodeCamp course, you will learn the basics of the Python 3 while building five projects. (Free Certification)

Python Django Web Framework – Full Course for Beginners

In this freeCodeCamp YouTube course, you will learn about Django templates, Django model forms, and class-based views.

Learn Python - Full Course for Beginners

In this freeCodeCamp YouTube Course, you will learn programming basics such as lists, conditionals, strings, tuples, functions, classes and more.

You will also build several small projects like a basic calculator, mad libs game, a translator app, and a guessing game.

The Python Handbook

In this Flavio Copes article, you will learn about strings, lists, tuples, recursion, and more.

You will also learn how to install 3rd party packages and how to work with virtual environments.

Python Tutorials for Absolute Beginners by CS Dojo

In this series of Beginner Python YouTube videos by CS Dojo, you will learn about dictionaries, loops, functions, objects and more.

You will also learn how to build a Twitter bot using Python.

Studytonight

In Studytonight, you will learn about Python basics, error handling, OOP, file handling, complex data types, Multithreading and more.

Once you have learned the basics, you can move onto their other modules which include the NumPy library, Matplotlib, Tkinter, Network Programming in Python, and Web Scraping using Beautiful Soup.

Python Core

In SoloLearn's Python Course, you will learn about strings, variables, OOP, functional programming and more. There are plenty of quizzes, challenges, and projects that you can build along the way.

In order to get started, you will need to create a free account.

Python Basics with Sam (freeCodeCamp)

In this Sam Focht YouTube Series, you will learn about loops, functions, strings, recursion and more.

You will also build several projects including a guessing game, shopping list, a board game, and a random password generator.

Python Beginner Tutorials

Once you cover the basics, you can move onto machine learning, databases, and GUI's.

Python Tutorial

In this PythonForBeginners tutorial, you will learn about functions, loops, lists, conditionals, error handling and more.

Once you learn the basics, you can explore the other modules on the site including Web Scraping with BeautifulSoup and Using the YouTube API in Python.

Automate the Boring Stuff with Python

In the Automate the Boring Stuff with Python online book, you will learn about dictionaries, strings, debugging, regular expressions and more.

If you prefer a video format, then you can go through the YouTube series that Al Sweigart put together.

Python Crash Course for Beginners

In this Brad Traversy YouTube course, you will learn about lists, tuples, dictionaries, functions, classes and more. Brad will also show you how to work with files and JSON data.

Python Tutorial - Python for Beginners

In this Programming with Mosh YouTube course, you will learn programming basics like variables, loops, strings, tuples, functions, classes and more.

You will also build three projects: one on automation, one on machine learning, and one on building a website with Django.

For additional practice, you can go through Mosh's 53 Python Exercises for Beginners.

PySpark Tutorial

In this freeCodeCamp YouTube course, you will learn about PySpark dataframes, PySpark GroupBy and aggregate functions, databricks, and more.

Python Backend Web Development Course (with Django)

In this freeCodeCamp YouTube course, you will learn about the basics of Python and Django. You will also build a blog, weather app, and a Realtime Chat App.

Flask Course - Python Web Application Development

In this freeCodeCamp YouTube course, you will learn about Flask forms, templates, validations and more by building your own e-commerce website.

Mobile App Development Courses

Android Development for Beginners – Full Course

In part 1 and part 2 of this freeCodeCamp YouTube course, you will learn how to build an Android application using Java.

React Native Tutorial for Beginners – Build a React Native App [2020]

In this Programming with Mosh course, you will learn how to build an iOS and Android app using React Native.

Kotlin Course – Tutorial for Beginners

In this freeCodeCamp YouTube course, you will learn about basic Kotlin functions, class methods, higher-order functions, and the Kotlin standard library.

Swift Programming Tutorial for Beginners

In this Code with Chris course, you will learn about the basics of Swift like variables, constants, data types, functions, and classes.

Game Development Courses

CS50's Introduction to Game Development

In this Harvard course, you will learn how to work with popular game engines like LÖVE 2D and Unity. You will also work with the Lua and C# programming languages.

Learn Unity – Beginner's Game Development Tutorial

In this freeCodeCamp YouTube course, you will learn how to get started building games using the Unity game engine.

C, C++, C# Courses

C Programming Tutorial for Beginners

In this freeCodeCamp YouTube course, you will learn about pointers, memory, functions, arrays and more.

C++ Tutorial for Beginners - Full Course

In this freeCodeCamp YouTube course, you will learn about pointers, inheritance, arrays, conditionals and more.

C# Tutorial - Full Course for Beginners

In this freeCodeCamp YouTube course, you will learn about conditionals, strings, objects, arrays, and more.

C Course

In this SoloLearn course, you will learn about data types, arrays, pointers, loops, strings, unions, memory management and more.

C++ Course

In this SoloLearn course, you will learn about pointers, conditionals, functions, classes, objects, polymorphism and more.

C# Course

In this SoloLearn course, you will learn about arrays, strings, structs, enums and more.

Java Courses

Java Programming: Solving Problems with Software

In this Coursera course, you will learn about classes, conditionals, loops, functions and more. You will also learn how to work with CSV files in Java and build a mini project.

Java Programming: Arrays, Lists, and Structured Data

In this Coursera course, you will learn about arrays, cryptography, HashMaps, and more. You will also build a mini project about the Vigenère cipher.

Java Programming: Principles of Software Design

In this Coursera course, you will learn about different sorting algorithms, and the basics of predictive text.

Java Programming Basics

In this Udacity course, you will learn about arrays, objects, classes, loops, debugging, and more.

Once you finish the beginner course, then you can take this intermediate Object Oriented Programming course.

Java Programming

In this Test Automation University course, you will learn about classes, loops, switch statements, conditionals, arrays, strings, abstraction and more.

Intro to Java Programming Course for Absolute Beginners

In this freeCodeCamp YouTube course, you will learn about arrays, objects, classes, loops, debugging, and more.

Learn Functional Programming in Java

In this freeCodeCamp YouTube course, you will learn about the properties of functional programming, callbacks, functional interfaces, combinator pattern, lambdas, and more.

Java Virtual Machine Architecture Explained for Beginners

In this freeCodeCamp article, you will learn about the Java Virtual Machine as well as the architecture behind it.

Java Tutorial for Beginners [2020]

In this Programming with Mosh YouTube course, you will learn about strings, arrays, conditionals, loops and more. You will also build a mortgage calculator.

Spring Boot Tutorial for Beginners (Java Framework)

In this freeCodeCamp YouTube course, you will learn the basics of how to use this popular Java framework.

Java Testing - JUnit 5 Crash Course

In this freeCodeCamp YouTube course, you will learn about JUnit Architecture, conditional executions, assumptions and more.

Java Course

In this SoloLearn course, you will learn about arrays, objects, classes, loops, and more.

PHP Courses

PHP Programming Language Tutorial - Full Course

In this freeCodeCamp YouTube course, you will learn about loops, functions, classes, objects, and more.

PHP For Absolute Beginners

In this Brad Traversy YouTube tutorial, you will learn about objects, loops, arrays and more. You will also build a basic CRUD (create, read, update, delete) application.

Use PHP to Create an MVC Framework - Full Course

In this freeCodeCamp YouTube course, you will learn how to work with file systems, custom routing, third party packages using composer, and more.

Ruby on Rails Courses

Learn Ruby on Rails - Full Course

In this freeCodeCamp YouTube course, you will learn how to make a Friends List App using Ruby on Rails.

Full Stack Ruby on Rails

In this Odin project curriculum, you will learn about Ruby, relational databases, Ruby on Rails, and more.

Databases

Relational Database freeCodeCamp Curriculum

In September of 2021, freeCodeCamp released the beta version of their relational database curriculum. This beta version is run entirely in Visual Studio Code using Docker and a CodeRoad extension.

In this course, you will learn about Git, GitHub, Bash, Nano, SQL, PostgreSQL and more. This is an entirely project-based learning curriculum.

Some of the projects that you will build in the course include a Video Game Character database, World Cup database, Celestial Bodies database, and a Bike rental shop.

To learn more about it, you can read through this article by Tom Mondloch who created the course.

SQL Tutorial - Full Database Course for Beginners

In this freeCodeCamp YouTube course, Mike Dane will teach you the basics of SQL. You will learn about creating tables, inserting data, wildcards, unions, joins and more.

In this course, you will learn how to install MySQL on your Mac or Windows computer. You will also practice your SQL skills by building a company database and an ER diagram.

If you like this course by Mike Dane, then please check out their YouTube channel for more free courses.

Learn SQL In 60 Minutes

This is a great course to take as a quick introduction to learning about the basics. From here you can move onto building your first few projects using SQL.

SQL For Beginners Tutorial

If you enjoy this free YouTube course by Nelson, then you can check out his other courses on his channel or take a look at his paid courses on his website.

MySQL Database - Full Course

Bharath also provides helpful resources to go along with the course including a getting started guide and GitHub repository of the MySQL scripts.

If you enjoyed this course, then you can visit other courses on their YouTube channel.

MySQL Tutorial for Beginners - Full Course

If you enjoy this course by Mosh, then you can visit their YouTube channel or his website for paid courses.

MySQL Crash Course | Learn SQL

This is a great course to take as a quick introduction to learning about the basics. From here you can move onto building your first few projects using MySQL.

Brad also includes a MySQL Cheat Sheet with this course.

SQL for Data Science

This course is free to audit on Coursera. It is also part of the Learn SQL Basics for Data Science Specialization.

If you are interested in continuing with the specialization, then I would suggest looking into the other three courses offered after this introductory course.

Database Systems - Cornell University Course (SQL, NoSQL, Large-Scale Data Analysis)

In this freeCodeCamp YouTube course, you will learn how to query database systems, index data, process queries, and more.

Here is part 2 of the course as well.

SQLite Databases With Python - Full Course

In this freeCodeCamp YouTube course, you will learn how to create tables, format results, update records, delete records and more.

Learn PostgreSQL Tutorial - Full Course for Beginners

In this freeCodeCamp YouTube course, you will learn about NULLIF, primary keys, foreign keys and more.

MongoDB Crash Course

In this Brad Traversy YouTube course, you will learn how to work with MongoDB shell, MongoDB atlas and more.

NoSQL Database Tutorial – Full Course for Beginners

In this freeCodeCamp YouTube course, you will learn about the basics of NoSQL and build two small projects.

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Front End Developer Roadmap

What is front end development?

How long does it take to become a Frontend Developer?

Should you learn everything covered in this learning path?

Essential Technologies for Frontend Development

Internet Basics

HTML

Visual Studio Code

CSS

JavaScript

Prompt Engineering

Version Control: Git and GitHub

Package Managers

Bootstrap 5 and SASS

JavaScript Frameworks (React, Vue, Angular, etc)

Tailwind CSS

Build Tools (Vite, etc)

Testing JavaScript (Jest, Cypress)

TypeScript

Web Security (OWASP)

GraphQL

Next.js

Astro

Performance Best Practices

React Native

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Video Walkthrough

Overview

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My Thoughts

Learn Git and GitHub in Spanish – Course for Beginners