School S11 · F02
LLM Engineering
Serve, evaluate and specialize large language models.
For engineers who need to go below the API — quantization, serving, distillation, fine-tuning and building custom model stacks.
Learning outcomes
What graduates can do.
- 01Serve open models at production latency and cost
- 02Fine-tune and align models to specific domains
- 03Distill and quantize for edge deployment
- 04Build in-house model gateways and routers
Curriculum
9 courses.
Delivered as a portfolio-based sequence. Every course culminates in shipped work reviewed by working practitioners.
- 01Transformer Architecture
- 02Tokenization, Context & Attention
- 03Inference Servers (vLLM, TGI, TensorRT-LLM)
- 04Quantization & Distillation
- 05SFT, DPO & RLHF
- 06Evals for LLMs
- 07Model Routing & Gateways
- 08Self-Hosting Open Models
- 09Capstone: Ship a Custom LLM Stack
Tools & technologies
vLLMTGIHugging Facellama.cppPyTorchOllama
Career tracks
- LLM Engineer
- Inference Engineer
- Foundation Model Team Engineer
Featured programs
Flagship programs anchored in this school.
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