BeginnerTechnical AI / ML (RAG-Focused)
Introduction to Retrieval-Augmented Generation (RAG)
Learn the fundamentals of RAG systems. Understand embeddings, vector search, and how to build simple RAG pipelines to enhance LLM accuracy with private data.
Prerequisites
- •Python programming basics
- •Basic understanding of APIs
- •Familiarity with LLMs (e.g., ChatGPT)
Course Outline
- 1.Why RAG exists – solving LLM knowledge limitations
- 2.Embeddings and vector search fundamentals
- 3.Building a simple RAG pipeline with LangChain
- 4.Vector databases – Pinecone, Weaviate, ChromaDB
- 5.Document chunking strategies
- 6.Common RAG tools and frameworks overview
Learning Outcomes
- ✓Understand RAG architecture and use cases
- ✓Build a basic RAG system from scratch
- ✓Work with embeddings and vector databases
- ✓Implement document retrieval pipelines
Ready to Get Started?
Request training for your team or schedule a consultation with our instructors.