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Learn AB Testing - Core Data Scientist Skills
Rating: 4.7 out of 5(32 ratings)
255 students

Learn AB Testing - Core Data Scientist Skills

Learn Statistical Concepts, A/B test Design, Metrics Design, Tool, and Launch Decision
Created byElly Qi Liu
Last updated 11/2025
English

What you'll learn

  • Foundation: Apply Statistical Concepts to Make Data-Driven Decisions - Translate goals into a testable hypothesis - Accurately interpret test results
  • Execution: Design, Run, and Scale Robust A/B Tests - Set up an experiment by calculating sample size and selecting key metrics
  • Tool: Introduce Commonly Used Industry-Standard AB test Platforms
  • Career Advancement: A/B Testing in Interviews - Confidently and efficiently answer the most common A/B testing interview questions

Course content

5 sections • 16 lectures • 49m total length

  • Introduction2:04

    Learn the fundamentals of a/b testing as a controlled, split test that compares version a to version b, follows a four-step setup, and applies real-world case studies for growth.

  • Introduction

Requirements

  • No statistics and programming needed. You will learn anything you need to know.

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.

Who this course is for:

  • 1) Data Professionals: Analysts and Scientists who want to specialize in A/B testing and build a rigorous foundation in experimental design.
  • 2) Cross-Functional Teams: Product Managers, Marketers, Designers, and Operations professionals who need to run and interpret experiments using A/B testing platforms.
  • 3) Business Leaders & Entrepreneurs: Founders, executives, and managers who aim to drive growth and improve service quality by building a data-driven experimentation culture.

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