Ultimate AB Testing Course with Python Coding

Ultimate AB Testing Course with Python Coding, available at $69.99, has an average rating of 4.46, with 74 lectures, based on 162 reviews, and has 738 subscribers.

You will learn about 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 This course is ideal for individuals who are Beginner data scientists seeking to learn AB testing or Job seekers preparing for data science interviews or Business, product and marketing leads learning to apply AB testing It is particularly useful for Beginner data scientists seeking to learn AB testing or Job seekers preparing for data science interviews or Business, product and marketing leads learning to apply AB testing.

Enroll now: Ultimate AB Testing Course with Python Coding

Summary

Title: Ultimate AB Testing Course with Python Coding

Price: $69.99

Average Rating: 4.46

Number of Lectures: 74

Number of Published Lectures: 74

Number of Curriculum Items: 74

Number of Published Curriculum Objects: 74

Original Price: $84.99

Quality Status: approved

Status: Live

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

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

Target Audiences

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

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 hoursof 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.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Getting Started

Chapter 2: Understand the Business Problem

Lecture 1: Understand the Business Problem

Lecture 2: Experiment Goals

Lecture 3: Key Members

Lecture 4: Product KPI

Lecture 5: The North Star Metric

Lecture 6: Driver Metric

Lecture 7: Guardrail Metrics

Lecture 8: Secondary Metrics

Lecture 9: Segmentation Metrics

Lecture 10: Launch Criteria

Lecture 11: Experiment Data

Lecture 12: Exercise – Amazon AB Testing (Question)

Lecture 13: Exercise – Amazon AB Testing (Solution)

Lecture 14: Code Walkthrough

Chapter 3: State the Experiment Hypothesis

Lecture 1: State the Experiment Hypothesis

Lecture 2: Hypothesis Statement

Lecture 3: Hypothesis Statement – Question 1

Lecture 4: Hypothesis Statement – Solution 1

Lecture 5: Hypothesis Statement – Question 2

Lecture 6: Hypothesis Statement – Solution 2

Lecture 7: Significance Level

Lecture 8: Significance Level – Question

Lecture 9: Significance Level – Solution

Lecture 10: Statistical Power

Lecture 11: Statistical Power – Question 1

Lecture 12: Statistical Power – Solution 1

Lecture 13: Statistical Power – Question 2

Lecture 14: Statistical Power – Solution 2

Lecture 15: Minimum Detectable Effect (MDE)

Lecture 16: Minimum Detectable Effect – Question 1

Lecture 17: Minimum Detectable Effect – Solution 1

Lecture 18: Code Walkthrough

Chapter 4: Design the Experiment

Lecture 1: Design the Experiment

Lecture 2: Randomization Unit

Lecture 3: Sample Size Calculation

Lecture 4: Sample Size Calculation – Question 1

Lecture 5: Sample Size Calculation – Solution 1

Lecture 6: Experiment Duration

Lecture 7: Experiment Duration – Question 1

Lecture 8: Experiment Duration – Solution 1

Lecture 9: Code Walkthrough

Chapter 5: Run the Experiment

Lecture 1: Run the Experiment

Lecture 2: Experiment Platform

Lecture 3: Peeking at P-Values

Lecture 4: Code Walkthrough

Chapter 6: Assess Validity Threats

Lecture 1: Assess Validity Threats

Lecture 2: Stable Unit Treatment Value Assumption

Lecture 3: Survivorship Bias

Lecture 4: Sample Ratio Mismatch

Lecture 5: Primacy Effect

Lecture 6: Novelty Effect

Lecture 7: Holiday Effect

Lecture 8: Other Effects to Consider

Lecture 9: AA Test

Lecture 10: Code Walkthrough

Chapter 7: Conduct Statistical Inference

Lecture 1: Conduct Statistical Inference

Lecture 2: Chi-Squared Test of Independence

Lecture 3: Chi-Squared Test of Independence – Question

Lecture 4: Chi-Squared Test of Independence – Solution

Lecture 5: Z-Test for Proportions

Lecture 6: Z-Test for Proportions – Question

Lecture 7: Z-Test for Proportions – Solution

Lecture 8: T-Test for Means

Lecture 9: T-Test for Means – Question

Lecture 10: T-Test for Means – Solution

Lecture 11: Code Walkthrough

Chapter 8: Launch Decision

Lecture 1: Decide Whether to Launch

Lecture 2: Absolute Difference vs Relative Difference

Lecture 3: Launch Decisions

Lecture 4: Decision Rule

Lecture 5: Confidence Interval

Lecture 6: Holdout Set

Lecture 7: Code Walkthrough

Instructors

Dan Lee
Data Science Coach (Former Google Data Scientist)

Rating Distribution

1 stars: 2 votes
2 stars: 2 votes
3 stars: 18 votes
4 stars: 57 votes
5 stars: 83 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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