Reinforcement Learning Explained

MOOC
Reinforcement Learning Explained
Language
English
Duration
2 months
Certificate
Certification paid
Course by EdX
Reinforcement Learning Explained
What will you learn?
Reinforcement Learning Problem
Markov Decision Process
Bandits
Dynamic Programming
Temporal Difference Learning
Approximate Solution Methods
Policy Gradient and Actor Critic
RL that Works
About the course

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.

Program
Reinforcement Learning Explained
Learn how to frame reinforcement learning problems, tackle classic examples, explore basic algorithms from dynamic programming, temporal difference learning, and progress towards larger state space using function approximation and DQN (Deep Q Network).
Lecturers
Jonathan Sanito
Jonathan Sanito
Senior Content Developer Microsoft
Roland Fernandez
Roland Fernandez
Senior Researcher and AI School Instructor, Deep Learning Technology Center Microsoft Research AI
Adith Swaminathan
Adith Swaminathan
Researcher Microsoft Research AI
Kenneth Tran
Kenneth Tran
Principal Research Engineer Microsoft Research AI
Katja Hofmann
Katja Hofmann
Researcher Microsoft Research AI
Matthew Hausknecht
Matthew Hausknecht
Researcher Microsoft Research AI
Platform
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