Ultimate AB Testing Course with Python Coding
Taught by a former Google Data Scientist, learn the theory and practice of AB testing based on real products
Ratings 4.51 / 5.00
What You Will Learn!
- How to Define the Business Goal of an AB Testing
- How AB Testing Problems are Solved at Companies like Google, Amazon and Meta
- How to Design an AB Testing and Interpret the Outcome
- How to Run Diagnostics to Assess the Validity of an AB Test (e.g. SRM)
- How to Solve AB Testing with Python (Pandas, Matplotlib, Numpy, Statsmodels)
- How to Prepare for Data Science Interviews with AB Testing Cases
Description
Welcome to Ultimate AB Testing Course with Python Coding
This is a course that will give you a hands-on experience in AB testing with Python. It's designed to help you think like a data scientist at top companies like Google, Amazon and much more.
Taught by a former data scientist at Google, the course contains 70+ lessons and 5 hours of video lectures and practice questions designed to teach you everything you need to know about the foundation of AB testing. Plus, the course contains bonus content including mock interview videos and practice cases based on interview questions seen in actual AB testing rounds.
What You Will Learn
The course is packed with core lessons on AB testing including:
Framing the Business Problem - how to define the business goal and KPIs of an experiment?
Defining the Metrics - What's the set of metrics to consider in an AB test? What about the North Star Metric, Primary Metric, Secondary Metric and Guardrail Metrics?
Stating the Business Hypothesis - How do you define the business and statistical hypothesis of an experiment?
Designing the Experiment - How do you set the experiment parameters including the significance level, statistical power, sample size and such?
Running the Experiment - What's the overview of infrastructure on how experiments run in large online platforms?
Checking for Validity - How do you assess whether the experiment result is valid or not? How do you check and address the Novelty Effect, Day of the Week Effect, SUTVA and much more?
Running Statistical Inference - What statistical tests do you use to assess the experiment result?
Interpret the Result - How do you make sound decisions based on AB testing results?
Hands-on Coding - You will get a chance to apply your learning with Python. Analyze a sample AB testing result with Matplotlib and Pandas and analyze results with Statsmodels.
How This Course Will Help You
You will learn the foundation of AB testing based on real-world cases
You will see how a practitioner approaches AB testing problems
You will get a chance to practice interview cases for product data science roles
This is a course I wish I had when I became a data scientist in 2016. I am confident that you find this course helpful in learning AB testing. I take the approach of explaining concepts in plain English and giving you illustrations based on actual cases seen in FAANG companies.
So, join the course now to become a data science pro.
Who Should Attend!
- Beginner data scientists seeking to learn AB testing
- Job seekers preparing for data science interviews
- Business, product and marketing leads learning to apply AB testing
