A/B testing is a well-known technique in web designing where designers apply it to test out different versions of the same webpage. The drawback to this technique is the waiting time to choose the best version and you lose the current performance of the webpage. To counter these drawbacks, you will learn how to build an AI Agent to A/B test the webpage in a much quicker pace using Reinforcement Learning.

This course will teach you how to build and deploy an AI Agent to test multiple versions of the web page and choose the best one much faster than the traditional A/B testing method. This quick decision-making will ensure good performance of your web-page even during the experiment.

By the end of this course, you will be able to deploy an AI Agent to perform an A/B test with many different strategies and to select the one which boosts its performance.

The code bundle for this video course is available at- https://github.com/PacktPublishing/Practical-Artificial-Intelligence-for-A-B-Testing-

Style and Approach

This course is a full hands-on tutorial. It shares only the essential theoretical concepts that will context and support the practical implementation of the solution. The essential theory is explained using examples, analogies, and figures to make it self-explanatory and as clear as possible. In the practical portion, all the codes are developed on the fly during the videos, each line is explained with minimum jargon. The main object is to make the viewers succeed and overcome obstacles in their own environments.