A B Testing in Python

Published 04/2022
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 27 lectures (2h 57m) | Size: 3 GB

Learn How To Define, Start, And Analyze The Results Of An A/B Test. Improve Business Performance Through A/B Testing

What you’ll learn
How to use A/B tests to improve business performance
Define A/B tests
Start A/B tests
Analyze the results of A/B tests
Measure the success of A/B tests
How to define a hypothesis
Design tracking for the metrics
How to prepare for a data science interview (when you get asked about A/B tests)
How to design A/B tests for digital products
Advanced considerations when you run multiple A/B tests at the same time

No experience in A/B testing is required
Knowledge of basic statistics
You do not need advanced statistical knowledge
Programming abilities are not required (but for some examples we will use Python)

A/B testing is a tool that helps companies make reliable decisions based on data.

This is one of the fundamental skills you need to land a job as a data scientist or data analyst.

Do you want to become a data scientist or a data analyst?

If you do, this is the perfect course for you!

Your instructor Anastasia is a senior data scientist working at a Stockholm-based music streaming startup. She has earned two Master’s degrees in Business Intelligence and Computer Science, and grown from a recent graduate to a Senior role in just 3 years. Anastasia has performed a significant number of A/B tests for large tech companies with hundreds of millions monthly users.

By taking this course, you will learn how to

· Define an A/B test

· Start an A/B test

· Analyse the results of an A/B test on your own

Along your learning journey Anastasia will walk you through an A/B testing process for a fictional company with a digital product. This case study unfolds throughout the course and touches on everything from the very beginning of the A/B testing process to the very end including some advanced considerations. Moreover, Anastasia takes some time to share with you her advice on how to prepare for the questions on the A/B test interview for a data scientist or data analyst position.

One strong point of differentiation from statistical textbooks and theoretical trainings is that these learning materials will teach you how to design A/B tests for digital products that have millions or hundreds of millions of users. It is a rare overview of the A/B testing process from a business, technical, and data analysis perspective.

This is the perfect course for you if you are

– a data science student who wants to learn one of the fundamental skills needed on the job

– junior data scientists with no experience with A/B testing

– software developers and product managers who want to learn how to run A/B tests in their company to improve the product they are building

You will learn an invaluable skill that can transform a company’s business (and your career along the way).

Who this course is for
Junior data scientists with no experience in A/B testing
Data science students with no working experience
Software developers
Product managers






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