Learn AB Testing – Core Data Scientist Skills

Learn Statistical Concepts, A/B test Design, Metrics Design, Tool, and Launch Decision

Description

You can start proving what works with A/B testing to find a better choice. A/B testing is the cornerstone of data-driven growth, and many teams are ready to move beyond basic button-color tests to experiments that deliver real business value.

This course provides the complete framework to take an A/B test from an initial hypothesis to a confident, scalable launch. Using case studies and clear explanations of statistical concepts, we give you a practical, end-to-end understanding of rigorous experimentation. You will master not just the theory behind A/B testing, but the strategic decision-making required to drive real product and revenue growth.

In this course, you will:

• Build a Statistical Foundation: Understand the core concepts—from populations & samples to confidence intervals & the Central Limit Theorem—that power valid experiments.

• Design for Impact: Learn to translate business goals into testable hypotheses, calculate precise sample sizes, and select the right metrics (primary, secondary, and guardrail) to measure success.

• Make Confident Decisions: Learn how to interpret results, calculate ROI, and make clear launch decisions across five common business scenarios.

Perfect for: Data Analysts / Scientists, Product Managers, Designers, Marketers, Operations, and business leaders who want to make data-informed decisions, eliminate guesswork, and systematically improve their product and business metrics.

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