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.
Jonathan Sanito, Roland Fernandez, Matthew Hausknecht, Katja Hofmann, Kenneth Tran and Adith Swaminathan
Amolcompleted 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 will have to refer to Sutton and Barto's book to clarify the concepts further. The parts of courses by Roland are most boring and not informative. It feels as if he simply reads the slides and i had given up on the course. All other instructors, Adith, Kenneth, Katja and Matthew are very good and the exceptional. The assignments are tough but fun and some questions in the assignments I felt at that point of time not clearly worded and confusing (perhaps it was my lack of understanding of some concepts).
To sum up, its a very good but difficult course to get started with reinforcement learning.