If you're feeling overwhelmed by the scattered knowledge about LLMs, this roadmap and curated resources from top sources are here to guide you. Dedicate 2-3 hours daily to understand the resources thoroughly, and by the fifth day, you'll be ready to develop your own LLM application! This roadmap is designed for individuals with basic machine learning knowledge. The optional content can be explored when time permits. Enjoy the learning journey! Once you've established your foundation, utilize this repository to delve into research papers, explore additional courses, and continue enhancing your skills.
Watch these videos (1 hour):
- LLM Foundations by FullStack (link)
Read these resources (1 hour):
- Applied LLMs Mastery course week 1 content (link)
- Applications of LLMs article by CellStrat (link)
- What are LLMs article by Amazon (link)
- (Optional) A survey of LLMs paper(link)
Watch these videos (1 hour):
- Prompt engineering course by Deeplearning.AI (link)
Read these resources (1 hour):
- Applied LLMs Mastery week course 2 content (link)
- Introduction to prompt engineering guide (link)
- Advanced prompt engineering techniques guide (link)
Watch these videos (30 mins):
- What is RAG by Deeplearning.AI (link)
- Building production ready RAG applications course by LlamaIndex (Link)
- (Optional) RAG with pinecone and Langchain video (link)
Read these resources (1 hour):
- Applied LLMs Mastery course week 4 content (link)
- RAG blog post by Amazon (link)
- Blog on advanced RAG techniques by Akash (link)
Watch these videos (1.5 hours):
- LLM Fine-Tuning Deeplearning.AI (link)
- Advanced fine-tuning techniques on YouTube by Shaw (link)
Read these resources (1 hour):
- Applied LLMs Mastery course week 3 content (link)
- Guide for fine-tuning LLMs by Labellerr (link)
- PEFT methods by HuggingFace (link)
Watch these videos (1 hour):
- Build your own LLM application using LangChain course by Deeplearning.AI (link)
Read these resources (1 hour):