Discover how to build an intelligent agent that can retrieve, reason, and remember. In this hands-on course, you will create an agentic RAG (retrieval-augmented generation) system that connects a language model to real-world data to enable dynamic question answering and discovery. You will start by setting up your development environment and preparing a dataset, then build an agent capable of autonomous reasoning, retrieval, and long-term memory.
Along the way, you will extend your agent with custom tools for translation, analysis, and pattern detection to transform it into a research assistant. By the end of the course, you will have a working interactive agent that can chat with your data and a clear blueprint for adapting agentic RAG systems to real-world use cases.
