A/B Testing and Experimentation for Businesses

It covers the full lifecycle — formulating hypotheses, calculating sample sizes up front, designing controlled experiments, collecting data without peeking at results early, and interpreting the outcome correctly. That emphasis on the unglamorous parts (sample size, not peeking) is exactly what separates experiments you can trust from ones that just confirm what you hoped, and it's where most real A/B testing goes wrong.

It's a strong fit for anyone who runs experiments and needs to trust the conclusions, and a poor fit if you want a quick overview or you lack basic statistics. Udemy lists a high price but it's nearly always $12–20 on sale with lifetime access — wait for the discount. Its completion certificate documents the learning rather than certifying it (as of 2026).

This course covers the full A/B testing lifecycle: formulating hypotheses, calculating required sample sizes, designing controlled experiments, collecting data without peeking, and interpreting results with statistical rigor. Students learn the most common A/B testing mistakes — underpowered tests, multiple comparison problems, and novelty effects — and how to avoid them.