#252 · Primary category： Education & Research
LLM-Engineers-Handbook
The LLM's practical guide: From the fundamentals to deploying advanced LLM and RAG apps to AWS using LLMOps best practices
Project last updated：04/22/26
GitHub Stars
5.3K
Forks
1.3K
Contributors
10
License
MIT
Why we included this project
This is the companion codebase to the LLM Engineer's Handbook, and it reads like a real project rather than a collection of isolated examples. You work through data collection and generation, fine-tuning a model, wiring up a RAG system, and deploying the whole thing to AWS, with monitoring and a testing framework included along the way. The repository is actively maintained, so the code has moved past what's printed in the book, which is a genuine advantage when you're following along. For a small team wanting to see how an LLMOps pipeline.
Articles for this project
No articles for this project yet.
To suggest a topic or contribute an article, contact us.
Related projects in this category
prompts.chat
f.k.a. Awesome ChatGPT Prompts. Share, discover, and collect prompts from the community. Free and open source — self-host for your organization with complete privacy.
JavaGuide
Java Interview & Backend General Interview Guide, covering computer fundamentals, databases, distributed systems, high concurrency, system design, and AI application development.
system-prompts-and-models-of-ai-tools
A curated collection of system prompts, internal tools, and AI models from popular AI assistants and coding agents.
30-seconds-of-code
Coding articles to level up your development skills
generative-ai-for-beginners
21 Lessons, Get Started Building with Generative AI