All courses
Guided Course
shipopsarchitecture
LLMOps: Serving and Operating LLMs
Model serving, inference optimization, guardrails, observability, and cost control — the engineering that keeps LLM systems running.
0/17
17 lessons
- 1. The model serving stack7 min
- 2. vLLM and production model servers9 min
- 3. Inference optimization10 min
- 4. Model compression: PTQ, QAT, and calibration7 min
- 5. Pruning and distillation6 min
- 6. Streaming and real-time delivery8 min
- 7. Building LLM APIs8 min
- 8. Model routing and fallbacks9 min
- 9. Caching strategies9 min
- 10. Input guardrails8 min
- 11. Output guardrails9 min
- 12. The OWASP Top 10 for LLM applications10 min
- 13. LLM observability7 min
- 14. Cost control7 min
- 15. Capacity planning and scaling7 min
- 16. Incident response and runbooks7 min
- 17. Capstone — a production LLM service9 min
- Key takeaways4 min
- How to get certified3 min
- Your certificate
About Nybble™
The AI space moves fast.
Nybble™ is how you keep up — and stay sharp.
Snack
What happened. In two minutes.
The AI news cycle moves at a pace no one can keep up with. Snack distills what launched, what shipped, and what matters — every day, without the filler.
Go to SnackStack
The concepts behind the headlines.
News tells you what. Stack tells you why and how. From RAG architectures to agentic evals, these are the ideas that will shape what you build next.
Go to StackHack
Prove you actually get it.
Reading about LangChain is not the same as knowing it. Hack challenges you with production-grade questions, then shows you the references that make the answer stick.
Go to Hack