Course
Customer Analytics and A/B Testing in Python
IntermediateSkill Level
Updated 01/2023PythonProbability & Statistics4 hr16 videos49 Exercises3,750 XP33,313Statement of Accomplishment
Create Your Free Account
or
By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.Loved by learners at thousands of companies
Training 2 or more people?
Try DataCamp for BusinessCourse Description
Prerequisites
Data Manipulation with pandasIntroduction to Functions in Python1
Key Performance Indicators: Measuring Business Success
This chapter provides a brief introduction to the content that will be covered throughout the course before transitioning into a discussion of Key Performance Indicators or KPIs. You'll learn how to identify and define meaningful KPIs through a combination of critical thinking and leveraging Python tools. These techniques are all presented in a highly practical and generalizable way. Ultimately these topics serve as the core foundation for the A/B testing discussion that follows.
2
Exploring and Visualizing Customer Behavior
This chapter teaches you how to visualize, manipulate, and explore KPIs as they change over time. Through a variety of examples, you'll learn how to work with datetime objects to calculate metrics per unit time. Then we move to the techniques for how to graph different segments of data, and apply various smoothing functions to reveal hidden trends. Finally we walk through a complete example of how to pinpoint issues through exploratory data analysis of customer data. Throughout this chapter various functions are introduced and explained in a highly generalizable way.
3
The Design and Application of A/B Testing
In this chapter you will dive fully into A/B testing. You will learn the mathematics and knowledge needed to design and successfully plan an A/B test from determining an experimental unit to finding how large a sample size is needed. Accompanying this will be an introduction to the functions and code needed to calculate the various quantities associated with a statistical test of this type.
4
Analyzing A/B Testing Results
After running an A/B test, you must analyze the data and then effectively communicate the results. This chapter begins by interleaving the theory of statistical significance and confidence intervals with the tools you need to calculate them yourself from the data. Next we discuss how to effectively visualize and communicate these results. This chapter is the culmination of all the knowledge built over the entire course.
Customer Analytics and A/B Testing in Python
Course Complete
Earn Statement of Accomplishment
Add this credential to your LinkedIn profile, resume, or CVShare it on social media and in your performance reviewEnroll Now
FAQs
Does this course teach how to design an A/B test from scratch?
Yes. Chapter 3 covers the full design process, from choosing an experimental unit to calculating the required sample size, along with the underlying statistical theory.
What are KPIs and how do they fit into this course?
Key Performance Indicators are metrics that measure business success. The first chapter teaches you to identify, define, and calculate meaningful KPIs as the foundation for later A/B testing.
Which Python libraries are used for the analysis?
You primarily use pandas for data manipulation and datetime handling, along with visualization libraries. The course also introduces statistical functions needed for hypothesis testing.
Will I learn how to interpret and communicate A/B test results?
Yes. The final chapter covers statistical significance, confidence intervals, and effective visualization techniques for presenting results to business stakeholders.
What kind of professional would benefit most from this course?
Data analysts, product analysts, and growth marketers who need to measure customer behavior, run experiments, and make data-driven business decisions will find this course directly applicable.
Join over 19 million learners and start Customer Analytics and A/B Testing in Python today!
Create Your Free Account
or
By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.Grow your data skills with DataCamp for Mobile
Make progress on the go with our mobile courses and daily 5-minute coding challenges.