Hi everyone!
My name is Anastasia. I’m a senior data scientist, currently working at a Stockholm-based music streaming startup. In my work on product performance analysis, I regularly leverage A/B testing and other statistical methods to uncover the optimal course of development for a digital product. As a result, I’ve completed hundreds of A/B tests for companies with over 300 million users a month in spheres ranging from mobile gaming to fintech.
I’ve always wanted to share my knowledge with people who seek professional growth in that direction. That’s why I’m very excited to announce that my A/B Testing in Python course with 365 Data Science is now live!
In what follows, I’ll lay out the main strong points of A/B testing as a decision-making tool and give you a breakdown of the actionable skills this course will equip you with.
The 365 Data Science A/B Testing in Python Course
Why A/B Testing in Python?
From Google trying out 50 different shades of blue for their CTA to Facebook rearranging their entire feed – there is no doubt that A/B testing is the must-have tool behind most of the data-driven decisions that define billion-dollar digital products today. Even if you have no advanced statistical knowledge or coding skills, by the end of this course you will be adept at independently carrying out A/B tests. Designed to give you a competitive edge, the course features hands-on exercises and real-world business cases with hundreds of millions of users, as well as a dedicated section for A/B testing interview prep.
Who Is This Course for?
If you are a data science student who’s just starting out with programming languages, a junior analyst with no prior experience in A/B testing, or if you’re looking to break into software development or product management, this course will equip you with the most in-demand skills for optimizing digital products.
What will you learn in this course?
Under my guidance you’ll learn:
- How to define A/B testing
- Its applications in the decision-making process
- Ways to identify opportunities for A/B testing
- Hands-on A/B test design and analysis
- How to determine metrics and KPIs
- Data tracking and measuring the success of A/B tests
- How to handle unconventional A/B testing interview questions
- Advanced considerations from multimillion-user business cases
Ready to Start A/B Testing in Python?
Visit the A/B Testing in Python course page to find more details about its curriculum or sign up below to try it out for free.
