MOC - LLMs
MOC - LLMs
Map of Content for Large Language Models and related topics.
Foundations
- 53.27 Learning about LLMs
- 53.29 LLM Architecture
- 53.40 Differences between an LLM and LM
- 53.41 Evolution of Language Models
- 53.44 Self Attention Mechanism
RAG (Retrieval Augmented Generation)
- 53.11 RAG course materials
- 53.12 RAG Evaluation
- 53.33 RAG
- 53.26 Large Language Models with Semantic Search
Prompt Engineering
- 53.17 ChatGPT Prompt Engineering for Developers
- 53.18 ChatGPT Prompts
- 53.50 Use cases of Prompt Engineering, RAG, and Fine Tuning
- 53.52 AI Agents Prompting Guide
LangChain & LangGraph
- 53.13 Building Systems with the ChatGPT API
- 53.14 Chatbot with LCEL
- 53.22 Functions, Tools and Agents with LangChain
- 53.24 LangChain Chat with Your Data
- 53.25 LangChain for LLM Application Development
- 53.38 AI Agents in Langraph
- 53.42 LangGraph
- 53.45 Unleashing the Power of LangChain Expression Language (LCEL) From Proof of Concept to Production
Evaluation
- 53.20 Evaluating LLM-based Applications
- 53.21 Evaluation for Large Language Models and Generative AI - A Deep Dive
- 53.32 LLMs for Evaluating LLMs
Production & Fine-Tuning
- 53.30 LLM from prototype to Production
- 53.43 Lessons learnt from building with LLMs
- 53.46 What We Learned from a Year of Building with LLMs (Part I)
- 53.47 Self Hosted LLMs
- 53.49 Train and Fine Tune LLMs for Production
