Session 4 : <em>Harnessing Local LLMs: A Practical Guide for Secure Data Science</em>

The adoption of Large Language Models (LLMs) for data analysis often raises privacy and security concerns due to reliance on cloud services. This talk explores running LLMs locally to address these challenges, comparing performance across three different hardware configurations. Attendees will learn about the development of a custom data analysis tool incorporating local LLMs and see a live demonstration of its capabilities. The session emphasizes practical strategies for integrating open source LLMs locally, enabling secure and efficient analysis of sensitive data.