Getting Started with AI for Spatial Data
Date and Time
Location
This 2-hour interactive workshop introduces participants to the practical use of Large Language Models (LLMs) for text classification tasks using real-world geotagged Twitter data. Participants will learn how to leverage Python and the LM studio to interact with advanced AI models such as Gemini, gaining foundational experience in calling Open AI APIs, designing effective prompts, and integrating LLMs into data workflows.
Through guided, hands-on exercises, attendees will explore how LLMs can be applied to classify and interpret geotagged social media data, uncovering patterns and insights from location-based text. The session will cover essential steps including dataset preparation, prompt design, model interaction, and result analysis. By the end of the workshop, participants will have developed a working understanding of how to apply LLMs for geospatial text analytics and will be equipped with transferable skills for building their own Gen AI-driven data projects.
This workshop is free for Harvard affiliates with a valid Harvard ID, and is $100 for others.
How to Apply:
- For Harvard Affiliates, please submit your application by filling out the Harvard affiliate form (HUID login required).
- For Non-Harvard applicants, please submit your application by filling out the Non-Harvard affiliate form. See this link for payment instructions.
On these forms, make sure to choose Getting Started with AI for Spatial Data as the workshop name.