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Reinforcement Learning

From bandits to deep RL. Policy gradients, Q-learning, actor-critic, RLHF, and real-world applications.

12 chaptersFirst 2 chapters free to previewPremium tier

After this course, you'll be able to:

Implement Q-learning, policy gradients, and actor-critic from scratch
Train AI from human feedback (RLHF — the technique behind ChatGPT)
Build multi-agent RL systems
Deploy RL in production applications

Full syllabus

1

Foundations

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2

Dynamic Programming

3

Monte Carlo Methods

4

Temporal Difference

5

Function Approximation

6

Policy Gradient

7

Advanced Policy Optimization

8

Model-Based RL

9

Multi-Agent RL

10

RLHF

11

Applications

12

Production Deployment

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