To support our site, Class Central may be compensated by some course providers.

Introduction to Reinforcement Learning

Higher School of Economics via Coursera

students interested
  • Provider Coursera
  • $ Cost Free Online Course (Audit)
  • Session Finished
  • Language English
  • Certificate Paid Certificate Available
  • Start Date

Taken this course? Share your experience with other students. Write review

Sign up to Coursera courses for free Learn how

The goal of «Intro to Reinforcement learning» is in its name: introduce students to reinforcement learning – the prominent area of modern research in artificial intelligence. The reinforcement learning differs much from both supervised and unsupervised learning and is more about how humans learn in reality.
Students will learn from this course both theoretical core and recent practical RL methods. Most importantly, they will learn how to apply such methods to practical problems. In six weeks students will be guided through the basics of Reinforcement Learning (RL): we will talk about essential theory of RL, value-based methods (such as SARSA and Q-learning), policy based algorithms and methods, designed to solve the optimal exploration problem. In addition to algorithms and theory, during the course we will also present useful practical tips and tricks, needed for learning stabilization, and study how to apply the methods to large scale problems with deep neural networks.

Taught by

Pavel Shvechikov and Alexander Panin

Highest Rated Courses

Reviews for Coursera's Introduction to Reinforcement Learning
Based on 0 reviews

  • 5 star 0%
  • 4 star 0%
  • 3 star 0%
  • 2 star 0%
  • 1 star 0%

Did you take this course? Share your experience with other students.

Write a review

Class Central

Get personalized course recommendations, track subjects and courses with reminders, and more.