- Reinforcement Learning
- Decision Support Systems
- Probability Distribution
- Artificial Intelligence and Machine Learning (AI/ML)
- Statistical Methods
- Markov Model
- Machine Learning
- Data-Driven Decision-Making
- Algorithms
- Deep Learning
- Simulations
Decision Making and Reinforcement Learning
Completed by Mariia Verbytska
May 1, 2024
47 hours (approximately)
Mariia Verbytska'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
