The virtual course "Fundamentals of Reinforcement Learning - Virtual Course - Coursera", is a course with different contents and that offers video classes of Approx. 15 hours to complete. Explore its essential features, and click the orange button to get detailed information on the Coursera e-Learning platform
Reinforcement learning is a subfield of machine learning, but it is also a general purpose formalism for automated decision making and AI.
This course introduces you to statistical learning techniques in which an agent performs explicit actions and interacts with the world.
Understanding the importance and challenges of learning decision-making agents is of paramount importance today, with more and more companies interested in interactive agents and intelligent decision-making.
This course is an introduction to the fundamentals of reinforcement learning.
Upon completion of this course you will: - Formalize problems as Markov decision processes - Understand basic exploration methods and exploration/exploitation trade-off - Understand value functions, as a general purpose tool for optimal decision making - Know how to implement dynamic programming as an efficient solution approach to an industrial control problem This course teaches you the key concepts of Reinforcement Learning, underlying classical and modern algorithms in RL.
After completing this course, you will be able to start using RL for real world problems, where you have or can specify the MDP.
This is the first course of the Reinforcement Learning Specialization.
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*You save up to USD$500 in 12 months, when you go from paying USD$59 for a monthly subscription, to an annual subscription with the promotion. The normal annual subscription is USD $399. With the promotion you will only pay USD $299. Find out everything by clicking the yellow button.
University of Alberta
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