Linear algebra is a useful skill for professionals in data science, machine learning, and AI. We just posted a course on the YouTube channel that will teach you linear algebra.

This crash course spans just over 6 hours and is a great starting point for beginners. It serves as the foundation for mastering linear algebra and sets you up for success in more advanced topics.

Tatev Aslanyan created this course. She is a seasoned Data Science and AI professional with over half a decade of international experience.

The course combines academic-level material with industry insights, leveraging resources and textbooks. You'll see how university concepts seamlessly translate into practical applications. The course features practical examples, including a detailed one-hour walkthrough of solving systems of linear equations with Gaussian elimination by hand, a core technique in linear algebra.

Course Structure

The course is divided into the following sections:

  1. Introduction to the Course

  2. Linear Algebra Roadmap for 2024

  3. Course Prerequisites

  4. Refreshment: Real Numbers and Vector Spaces

  5. Refreshment: Norms and Euclidean Distance

  6. Why These Prerequisites Matter

  7. Foundations of Vectors

  8. Vector - Geometric Representation Example

  9. Special Vectors

  10. Application of Vectors

  11. Vector Operations and Properties

  12. Advanced Vectors and Concepts

  13. Length of a Vector - Definition and Example

  14. Length of Vector - Geometric Intuition

  15. Dot Product

  16. Dot Product, Length of Vector, and Cosine Rule

  17. Cauchy Schwarz Inequality - Derivation & Proof

  18. Introduction to Linear Systems

  19. Introduction to Matrices

  20. Core Matrix Operations

  21. Solving Linear Systems - Gaussian Elimination

  22. Detailed Example - Solving Linear Systems

  23. Detailed Example - Reduced Row Echelon Form (Augmented Matrix, REF, RREF)


This course offers a solid foundation in linear algebra, serving as a fantastic warm-up for anyone looking to explore generative AI in our upcoming courses. Watch the full course on the YouTube channel (6-hour watch).