Table of Contents
Best AB Testing Courses 2022
Best AB Testing Tutorials 2022
Bayesian Machine Learning in Python: A/B Testing
This course is entirely dedicated to A / B testing.
A / B tests are used everywhere. Marketing, retail, news feed, online advertising, etc.
A / B testing is about comparing things.
If you’re a data scientist and you want to tell the rest of the business that “logo A is better than logo B”, well, you can’t just say it without proving it with numbers and statistics.
Traditional A / B testing has been around for a long time and is full of confusing approximations and definitions.
In this course, as we do traditional A / B testing in order to appreciate its complexity, we will eventually come to the Bayesian way of doing things through machine learning.
First, we’ll see if we can improve traditional A / B testing with adaptive methods. All of this helps you solve the explore-exploit dilemma.
You will learn more about the epsilon-greedy algorithm, which you may have heard of in the context of reinforcement learning.
We will improve the epsilon-greedy algorithm with a similar algorithm called UCB1.
Finally, we will improve these two elements using a fully Bayesian approach.
Why are we interested in the Bayesian method in machine learning?
It’s a whole different way of thinking about probability.
This is a paradigm shift.
You will probably have to come back to this course several times before it fully penetrates.
It’s powerful too, and many machine learning experts often make statements about how they “fit into Bayesian school of thought.”
In summary, this is going to give us a lot of powerful new tools that we can use in machine learning.
The things you will learn in this course do not just apply to A / B testing, but rather, we use A / B testing as a real life example of how Bayesian techniques can be applied.
You will learn these fundamental tools of the Bayesian method – through the example of A / B testing – and you can then transpose these Bayesian techniques to more advanced machine learning models.
A/B Testing and Experimentation for Beginners
Find out what A / B testing is and how you can use it to make data-driven decisions to improve your marketing, conversion rate, and customer experience. The course will cover the fundamentals of A / B testing, provide you with the process you can use to start A / B testing today, as well as some examples to kickstart your creativity.
The applications for A / B testing are diverse, some
Product Changes – Web, Desktop, Mobile
Marketing messages
Landing page optimization
Creative design
Call to action
Funnel conversions
Search marketing
Conversion rate optimization (CRO)
Growth hacking
Find out how to set up an A / B test in Google Optimize
All major organizations such as Facebook, Google, Amazon, Microsoft, Twitter, etc. spend millions of dollars on A / B testing. Understand the basics so you can learn and apply too.
I have worked in several large organizations and have helped them deliver better marketing, better conversion, and better customer experience using the content I will be offering in this course.
Learn Google Optimize – Beginners – Free A/B Testing Tool
Google Optimize is a free testing and experimentation platform from Google (the paid version is called Google Optimize 360). Considering the great popularity of Google Analytics and the easy integration of Google Optimize with Google Analytics, it is one of the best tools for running A / B, MVT, and experimentation. Those who are looking for a new job, this tool with added value to your CV, then go ahead and sign up. In this course, you will learn everything you need to get started with experimentation. We will cover
Subscribe to Google Optimize
Understand accounts and containers
Configure the Google Optimize code
Create an A / B test
Create a redirect test
Create a multivariate test
A must have tool for digital marketers, digital analysts, growth hackers and conversion rate optimization professionals or anyone looking to enter these fields.