LLM Zoomcamp

Pre-requisites:

• Comfortable with programming and Python
• Comfortable with command line
• Docker
• No previous exposure to AI or ML is required

Syllabus

Pre-course workshops

Introduction

• build a simple Q&A system
• Video: https://www.youtube.com/watch?v=q-p36Ak6YI8
• Code: https://github.com/alexeygrigorev/llm-rag-workshop

Implement a search engine

• Video: https://www.youtube.com/watch?v=nMrGK5QgPVE
• Code: https://github.com/alexeygrigorev/build-your-own-search-engine

Introduction to LLMs and RAG

• LLMs and RAG
• Preparing the environment
• Retrieval and the basics of search
• OpenAI API
• Simple RAG with Open AI
• Text search with Elasticsearch

Open-source LLMs

• Getting an environment with a GPU
• Open-source models from HuggingFace Hub
• Running LLMs on a CPU with Ollama
• Creating a simple UI with Streamlit

Vector databases

• Vector search
• Creating and indexing embeddings
• Vector search with Elasticsearch

Workshop: dlt

LLM orchestration and ingestion pipelines

• Ingesting data with Mage

Monitoring and Guardrails

• Monitoring with ground-truth
• Metrics (RAGAs)
• Dashboarding with Grafana for visualization
• Monitoring chat
• Guardrails

Tips and Tricks for advanced RAG systems

• Best practices

Hands-on project