Module 11: RLHF & LLM Alignment

Coming soon.

Where RL meets large language models. RLHF is how ChatGPT learned to be helpful - and it's a surprisingly clean application of the policy gradient methods from earlier modules.

Learning Objectives

• Understand the RLHF pipeline (reward model + PPO fine-tuning)
• Implement a simple reward model
• Learn DPO and its relationship to RLHF
• Understand KL-constrained optimization and why it matters

Concept Explanation

Coming soon.

Code Examples

Coming soon.

Exercises

Coming soon.