This course introduces Retrieval-Augmented Generation (RAG), a practical approach that combines large language models with information retrieval to produce answers grounded in trusted sources rather than relying solely on the model’s internal knowledge.
In this course, we build and explore a complete RAG pipeline through practical examples and live demonstrations. We cover how documents are prepared for retrieval, how retrieval can be improved for more accurate and complete results, and how to evaluate whether a RAG system’s answers are actually grounded and trustworthy rather than simply plausible.
Live online classes will take place on Tues. Feb. 16, Fri. Feb. 19, and Tues. Feb. 23 from 1 P.M. to 2 P.M. Eastern Time. Recordings of live classes will be available afterwards in this course for self-paced learning and review.