Decision Making and Reinforcement Learning
Completed by Andrey Belogaev
January 12, 2026
47 hours (approximately)
Andrey Belogaev's account is verified. Coursera certifies their successful completion of Decision Making and Reinforcement Learning
What you will learn
Map between qualitative preferences and appropriate quantitative utilities.
Model non-associative and associative sequential decision problems with multi-armed bandit problems and Markov decision processes respectively
Implement dynamic programming algorithms to find optimal policies
Implement basic reinforcement learning algorithms using Monte Carlo and temporal difference methods
Skills you will gain
- Category: Data-Driven Decision-Making
- Category: Reinforcement Learning
- Category: Deep Learning
- Category: Decision Support Systems
- Category: Probability Distribution
- Category: Machine Learning
- Category: Algorithms
- Category: Statistical Methods
- Category: Simulations
- Category: Artificial Intelligence and Machine Learning (AI/ML)
- Category: Markov Model
