Created
Sep 1, 2025 10:05 PM
Tags
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
 
- Retrieval and the basics of search
 - OpenAI API
 - Simple RAG with Open AI
 
Open-source LLMs and self-hosting LLMs
- Simple RAG with Open-Source LLMs
 
Vector databases and retrieval techniques
- Embeddings
 - Vector search
 - Adding vectors to RAG
 
Workshop: dlt
- TBA
 
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
 
Competition
TBA
Hands-on project
To Open the Jupyter Online
jupyter notebook --port=46139
# or for JupyterLab
jupyter lab --port=46139docker run -d --name elasticsearch -p 9200:9200 -p 9300:9300 -e "discovery.type=single-node" docker.elastic.co/elasticsearch/elasticsearch:7.9.3