About the Instructor
DeepLearning.AI + OpenAI/Anthropic
Co-created with OpenAI and Anthropic researchers who built RLHF for ChatGPT and Claude. Covers production alignment techniques.
First Principles
Base LLMs generate text well but don't follow instructions or avoid harmful outputs. RLHF trains a reward model (human feedback) then uses RL to optimize the LLM to maximize rewards. Result: instruction-following, safe, aligned models.
AI Ecosystem Fit
Layer 4 (Models) → Production quality — RLHF is the difference between a toy chatbot and production ChatGPT. This is the most valuable technique in modern AI.
Prerequisites
What Paid Projects This Unlocks
Train aligned agents: use RLHF to optimize for safety, instruction-following, and human preferences. Deploy responsible AI.
3 Client Projects You Can Get Paid For
Real businesses have this problem right now. Build it, pitch it, charge for it.
Stack This With → (Unlocks Higher-Paying Projects)
Implement multi-objective RLHF (safety + performance)
Deploy aligned models in production
Monitor for reward hacking and drift
Why This Matters
RLHF is how OpenAI created ChatGPT. Every serious LLM uses RLHF. This is the skill that separates toy models from production systems.