Creating AI Applications using Retrieval-Augmented Generation (RAG)

Unlock the full potential of large language models (LLMs) by integrating external data sources through Retrieval Augmented Generation (RAG). This course will teach you to build AI systems that can search, retrieve, and cite information from documents, enabling more reliable and context-aware responses. You'll also learn how to create advanced AI-powered search applications with Streamlit and ChromaDB. Ideal for learners with a basic understanding of Python and machine learning concepts.

Syllabus

RAG Foundations: Learn how to give your large language model the powers of retrieval with RAG, an AI engineering technique used to give LLMs the power to search documents.

Lesson: RAG Foundations
Quiz: RAG Foundations Quiz

Build a RAG App: Build a RAG (Retrieval Augmented Generation) app using Streamlit, Chroma and OpenAI.

Lesson: Build a RAG App
Quiz: Build a RAG App Quiz

RAG Techniques: Explore Retrieval-Augmented Generation (RAG), a powerful way to retrieve documents for AI applications and a great step toward becoming an AI engineer.

Lesson: RAG Techniques
Quiz: RAG Techniques Quiz
Informational: Next Steps