Decision Making and Reinforcement Learning
Completed by Sebastian Winkler
April 10, 2026
47 hours (approximately)
Sebastian Winkler'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: Reinforcement Learning
- Category: Machine Learning Algorithms
- Category: Analysis
- Category: Algorithms
- Category: Machine Learning Methods
- Category: Decision Intelligence
- Category: Statistical Methods
- Category: Deep Learning
- Category: Artificial Intelligence and Machine Learning (AI/ML)
- Category: Markov Model
- Category: Machine Learning
