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MIT 6S191: Reinforcement Learning

Course Feature
  • Cost
    Free
  • Provider
    Youtube
  • Certificate
    No Information
  • Language
    English
  • Start Date
    2023-04-14
  • Learners
    No Information
  • Duration
    No Information
  • Instructor
    Alexander Amini
Next Course
2.5
37,208 Ratings
This MIT 6S191: Reinforcement Learning course provides an introduction to deep learning and its applications. Lecturer Alexander Amini will cover topics such as classes of learning problems, definitions, the Q function, deep Q networks, Atari results and limitations, policy learning algorithms, discrete vs continuous actions, training policy gradients, RL in real life, VISTA simulator, AlphaGo and AlphaZero and MuZero, and a summary. With all lectures, slides, and lab materials available online, this course is perfect for anyone interested in learning more about deep learning and its applications. Subscribe to stay up to date with new deep learning lectures at MIT, or follow us @MITDeepLearning on Twitter and Instagram to stay fully-connected!
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MIT 6S191: Reinforcement Learning Go to class
Course Overview

❗The content presented here is sourced directly from Youtube platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [July 21st, 2023]

MIT 6S191: Reinforcement Learning is an introduction to deep learning course offered by MIT. Lecturer Alexander Amini will provide an overview of the lecture, which includes an introduction to classes of learning problems, definitions, the Q function, Deep Q Networks, Atari results and limitations, policy learning algorithms, discrete vs continuous actions, training policy gradients, RL in real life, VISTA simulator, AlphaGo and AlphaZero and MuZero, and a summary. All lecture slides and lab materials can be found at http://introtodeeplearning.com. Students are encouraged to stay up to date with new deep learning lectures at MIT, or follow @MITDeepLearning on Twitter and Instagram to stay fully-connected.

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