A/B Testing in Python

Intermediate

Updated 12/2024

Learn the practical uses of A/B testing in Python to run and analyze experiments. Master p-values, sanity checks, and analysis to guide business decisions.

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Course Description

In this course, you will dive into the world of A/B testing, gain a deep understanding of the practical use cases, and learn to design, run, and analyze these A/B tests in Python.

Discover How A/B Tests Work

Did you know that you are almost guaranteed to participate in an A/B test every time you browse the internet? From search engines and e-commerce sites to social networks and marketing campaigns — all businesses hire the best data analysts, scientists, and engineers to leverage the power of AB testing. Testing different variants can help optimize the customer experience, maximize profits, inform the next best design, and much more.

Learn About A/B Testing in Python

You’ll start by learning how to define the right metrics before learning how to estimate the appropriate sample size and duration to yield conclusive results. Throughout this course, you’ll use a range of Python packages to help with A/B testing, including statsmodels, scipy, and pingouin.

By the end of the course, you will be able to run the necessary checks that guarantee accurate results, master the art of p-values, and analyze the results of A/B tests with ease and confidence to guide the most critical business decisions.

Prerequisites

Hypothesis Testing in Python

Overview of A/B Testing

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What is A/B testing?

Course Description

Discover How A/B Tests Work

Learn About A/B Testing in Python

Earn Statement of Accomplishment

FAQs

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Join over .css-nklxlk{color:var(--wf-brand--main, #03EF62);}15 million learners and start A/B Testing in Python today!

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Join over 15 million learners and start A/B Testing in Python today!