- Function Approximation
- Artificial Intelligence (AI)
- Intelligent Systems
- Statistical Programming
- Machine Learning Algorithms
- Machine Learning
- Python Programming
- Reinforcement Learning
Fundamentals of Reinforcement Learning
Completed by Mohamed Sami ASSENINE
October 24, 2021
15 hours (approximately)
Mohamed Sami ASSENINE'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
