BEGIN:VCALENDAR VERSION:2.0 METHOD:PUBLISH BEGIN:VEVENT UID:20260417T043638-1735288196-northwestern.edu DTSTAMP:20260417T043638 DTSTART:20250904T093000 DTEND:20250904T160000 SUMMARY:AI for Researchers: Enhancing LLM Systems with RAG (In-person) LOCATION:Big Ten Room, Norris University Center DESCRIPTION:Retrieval-Augmented Generation (RAG) is an approach to build Large Language Model (LLM) based systems which are grounded on an external knowledge base, such as a collection of academic papers, clinical data, books, or websites. In research, RAG is applied to a plethora of tasks, from improving medical diagnoses, to summarizing legal documents, to generating novel research ideas grounded on well-vetted and trusted sources. In this hands-on workshop, we will start by learning the basic framework and core elements of RAG, including embedding models, vector databases, indexing techniques, and generative models. We will then build a RAG system step by step and test it on provided datasets. \nPrerequisites: Basic familiarity with Python.\n\nPiP URL: https://planitpurple.northwestern.edu/event/629199 END:VEVENT END:VCALENDAR ORGANIZER:Northwestern IT Research Computing and Data Services