Advanced · every module free · 7 challenges
Objectives, scaling laws, compute-optimal training and how frontier models are actually built.
SFT, reward models, RLHF, DPO and the constitutional methods — how a base model becomes an assistant.
Context construction, decoding parameters, constrained generation and schema-valid output every time.
Chunking, embeddings, vector search, reranking and the evaluation that tells you whether any of it worked.
Tool calling, planning, multi-step execution, memory, and the failure modes that only appear in loops.
Benchmarks, model-graded evaluation, human review and building an eval set that actually predicts production.
Denoizing diffusion, latent diffusion, and the models that put images, audio and text in one system.