Fundamentals of Reinforcement Learning
Completed by Klym Popov
March 25, 2024
15 hours (approximately)
Klym Popov'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
- Category: Machine Learning Algorithms
- Category: Agentic systems
- Category: Decision Intelligence
- Category: Machine Learning
- Category: Reinforcement Learning
- Category: Algorithms
- Category: Markov Model
- Category: Artificial Intelligence
