The course Reinforcement Learning is an online class provided by Udacity. The skill level of the course is Advanced. It may be possible to receive a verified certification or use the course to prepare for a degree.
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.
Offered at Georgia Tech as CS 8803
Become a reinforcement learning expert
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.
Additionally, you will be programming extensively in Java during this course. If you are not familiar with Java, we recommend you review Udacity’s Object Oriented Programming in Java course materials to get up to speed beforehand.
See the Technology Requirements for using Udacity.
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.
To obtain a verified certificate from Udacity you have to finish this course or the latest version of it, if there is a new edition. The class may be free of charge, but there could be some cost to receive a verified certificate or to access the learning materials. The specifics of the course may have been changed, please consult the provider to get the latest quotes and news.
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