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# Data Science IV (course at WHZ)

The last part of the data science lecture series is devoted to reinforcement learning. Next to very basic techniques we also discuss state-of-the-art deep reinforcement learning with artificial neural networks.

## Reinforcement Learning

### Week 1 (Overview and Stateless Tasks)

Lectures

- Overview and Examples

  - What is Reinforcement Learning?

  - Examples

  - Maximization of Return

- Stateless Learning Tasks (Multi-armed Bandits)

Self-study

Projects and Exercises

- Modeling (exercises)

- Online Advertising (project)

### Week 2 (Markov Decision Processes)

Lectures

- Markov Decision Processes

  - Basic Notions

  - Bellman Equations and Optimal Policies

Self-study

Projects and Exercises

- Markov Decision Processes (exercises)

### Week 3 (Dynamic Programming)

Lectures

- Dynamic Programming

Self-study

Projects and Exercises

- Frozen Lake

  - Dynamic Programming (project)

### Week 4 (Monte Carlo Methods)

Lectures

- Monte Carlo Methods

Self-study

Projects and Exercises

- Frozen Lake

  - Monte Carlo Methods (project)

### Week 5 (Temporal Difference Learning)

Lectures

- Temporal Difference Learning (TD Learning)

Self-study

Projects and Exercises

- Frozen Lake

  - SARSA (project)

### Week 6 (Tic-Tac-Toe)

Lectures

Self-study

Projects and Exercises

- Q-Learning for Tic-Tac-Toe

### Week 7 (Approximate Methods)

Lectures

- Approximate Value Function Methods

  - Principal Approach

  - Policy Evaluation

  - Policy Improvement

Self-study

Projects and Exercises

### Week 8 (Cart Pole SARSA)

Lectures

Self-study

Projects and Exercises

- Cart Pole

  - The Cart Pole Environment

  - SARSA

### Week 9 (Deep Q-Learning)

Lectures

- Approximate Value Function Methods

  - Deep Q-Learning

Self-study

Projects and Exercises

- Cart Pole

  - Deep Q-Learning

### Week 10 (Policy Gradient Methods)

Lectures

- Policy Gradient Methods

Self-study

Projects and Exercises

### Week 11 (Policy Gradient Methods)

Lectures

Self-study

Projects and Exercises

- Cart Pole

  - Policy Gradient Method