A/B testing is a key technique used in data science for making data-driven decisions in business. We just published a course on the freeCodeCamp.org YouTube channel that will tech you this important data science technique.
Developed by Tatev, a seasoned data scientist from Lunar Tech, this comprehensive video course bridges the gap between theoretical knowledge and practical application, making it a great resource for data analysts and scientists looking to enhance their portfolios.
The course begins with an introduction to the essentials of data science and the specific role of A/B testing within the field. You will dive deep into the basics of A/B testing, learning about key parameters such as hypothesis testing, significance levels, and the critical aspects of pooled estimates, test statistics, p-values, and assessing statistical significance.
Following the foundational concepts, the course offers a detailed exploration of designing A/B tests with a data science approach. You will engage in formulating hypotheses and identifying primary metrics crucial for effective testing in real-world scenarios. This segment ensures a solid understanding of the theoretical underpinnings necessary for successful experimentation.
One of the features of the course is its integration of practical Python tutorials. The sections will give you the skills to implement A/B tests in real-world settings using Python. Techniques covered include loading data with Pandas, visualizing A/B test results using tools like Matplotlib and Seaborn, and performing power analysis and variance calculations relevant to A/B testing.
The course includes a 1.5-hour real-life case study featuring a business angle with LunarTech. You will be walked through an experiment on LunarTech’s landing pages, analyzing how minor changes, such as adjusting a button in the UX design, can significantly impact user engagement, as evidenced by the Click-Through Rate (CTR).
Tatev’s extensive experience as a data scientist and educator shines throughout the course, making complex topics accessible and engaging. By the end of the series, participants will not only have grasped the intricate details of A/B testing but will also be able to apply these insights effectively in their professional roles.
Watch the full course on the freeCodeCamp.org YouTube channel (2.5-hour watch).