About this Course

You should take this course if you have an interest in machine learning and the desire to engage with it from a theoretical perspective. Through a combination of classic papers and more recent work, you will explore automated decision-making from a computer-science perspective. You will examine efficient algorithms, where they exist, for single-agent and multi-agent planning as well as approaches to learning near-optimal decisions from experience. At the end of the course, you will replicate a result from a published paper in reinforcement learning.

Course Cost
Free
Timeline
Approx. 4 months
Skill Level
advanced
Included in Product

Rich Learning Content

Interactive Quizzes

Taught by Industry Pros

Self-Paced Learning

Student Support Community

Join the Path to Greatness

This course is your first step towards a new career with the Become a Machine Learning Engineer Program.

Free Course

Reinforcement Learning

byGeorgia Institute of Technology

Enhance your skill set and boost your hirability through innovative, independent learning.

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Course Leads

Charles Isbell

Charles Isbell

Instructor

Michael Littman

Michael Littman

Instructor

Chris Pryby

Chris Pryby

Instructor

Prerequisites and Requirements

Before taking this course, you should have taken a graduate-level machine-learning course and should have had some exposure to reinforcement learning from a previous course or seminar in computer science (students who have completed CS 7641 will be well prepared for this course).

Additionally, you will be programming extensively in Java during this course. If you are not familiar with Java, we recommend you review Udacity's Intro to Java Programming course materials to get up to speed beforehand.

See theTechnology Requirements for using Udacity.

Why Take This Course

This course will prepare you to participate in the reinforcement learning research community. You will also have the opportunity to learn from two of the foremost experts in this field of research, Profs. Charles Isbell and Michael Littman.

What do I get?
Instructor videosLearn by doing exercisesTaught by industry professionals