- Artificial Intelligence
- Machine Learning Algorithms
- Probability Distribution
- Algorithms
- Machine Learning
- Reinforcement Learning
- Markov Model
Fundamentals of Reinforcement Learning
Completed by Michael Fleicher
July 27, 2021
15 hours (approximately)
Michael Fleicher's account is verified. Coursera certifies their successful completion of Fundamentals of Reinforcement Learning
What you will learn
Formalize problems as Markov Decision Processes
Understand basic exploration methods and the exploration / exploitation tradeoff
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
Skills you will gain
