- Markov Model
- Algorithms
- Machine Learning
- Probability Distribution
- Reinforcement Learning
- Artificial Intelligence
- Machine Learning Algorithms
Fundamentals of Reinforcement Learning
Completed by José Eduardo Chillogalli Astudillo
May 7, 2024
15 hours (approximately)
José Eduardo Chillogalli Astudillo'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
