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Reinforcement Learning Explained

Microsoft via edX

This course may be unavailable.


Reinforcement Learning (RL) is an area of machine learning, where an agent learns by interacting with its environment to achieve a goal.

In this course, you will be introduced to the world of reinforcement learning. You will learn how to frame reinforcement learning problems and start tackling classic examples like news recommendation, learning to navigate in a grid-world, and balancing a cart-pole.

You will explore the basic algorithms from multi-armed bandits, dynamic programming, TD (temporal difference) learning, and progress towards larger state space using function approximation, in particular using deep learning. You will also learn about algorithms that focus on searching the best policy with policy gradient and actor critic methods. Along the way, you will get introduced to Project Malmo, a platform for Artificial Intelligence experimentation and research built on top of the Minecraft game.

edX offers financial assistance for learners who want to earn Verified Certificates but who may not be able to pay the fee. To apply for financial assistance, enroll in the course, then follow this link to complete an application for assistance.

Note: These courses will retire in June. Please enroll only if you are able to finish your coursework in time.

Taught by

Jonathan Sanito, Roland Fernandez, Matthew Hausknecht, Katja Hofmann, Kenneth Tran and Adith Swaminathan


5.0 rating, based on 1 Class Central review

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  • Profile image for Amol Nayak
    Amol Nayak

    Amol Nayak completed this course, spending 6 hours a week on it and found the course difficulty to be very hard.

    I liked the course as I progressed and completed it. The first two weeks are pretty smooth and then it starting getting tough. It cam be very frustrating at times as even after watching videos multiple times you may not understand some concepts. You…

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