- Markov Model
- Linear Algebra
- Reinforcement Learning
- Probability Distribution
- Artificial Intelligence
- Algorithms
- Machine Learning
Fundamentals of Reinforcement Learning
Completed by John F Porter
September 23, 2020
15 hours (approximately)
John F Porter'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
