Topics
- What is an LLM based system?
- How is an LLM based system different from a traditional software system?
- What is context, and how this context is provided to the LLM - prompts, RAG, MCP
- The 8 steps involved in end to end working of an LLM to output result of a query. - training using corpus, Tokenization, Embedding, Vector DB creation & RAG, Query & Prompts, Search, Retrieval, Output.
- What is an agentic AI system?
- What is Lanchain? The elements of langchain - Prompts, LLM, chain, Vector Db, Index, Memory state, data loader, data splitter: https://www.youtube.com/watch?v=1bUy-1hGZpI&t=241s
- What is Langraph? https://www.youtube.com/watch?v=qAF1NjEVHhY
- Code walkthrough
- Streaming in langchain - https://www.youtube.com/watch?v=gr5CGL4_jpY
- Build with langhcain playlist - https://www.youtube.com/watch?v=mmBo8nlu2j0&list=PLfaIDFEXuae06tclDATrMYY0idsTdLg9v
- Auto Prompt builder
- RAG app with type script
- SQL research agent
- skeleton of thoughts
- building a research assistant
- build and deploy RAG app with pinecone serverless
- build a web RAG chatbot using langchain
- open source RAG with Nomic’s new embedding model