- Artificial Intelligence
- Algorithms
- Probability Distribution
- Markov Model
- Reinforcement Learning
- Machine Learning
- Linear Algebra
Fundamentals of Reinforcement Learning
Completed by Fabian Kung
July 23, 2021
15 hours (approximately)
Fabian Kung'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
