October 12th, 4-6 pm, Online Workshop 2: LLMs for Data Analysis and Synthetic Annotation – for advanced users, technical audience, with Christopher Klamm, Language: German, Registration via google forms.

In this workshop, participants will learn how open and closed Large Language Models (LLMs) can be specifically applied to data analysis. The focus is on the automated evaluation, structuring, and enrichment of data through synthetic labels. Using practical examples (e.g., with Llama), the workshop demonstrates how LLMs are used for classification, scoring, or qualitative assessments. This session is designed for anyone looking to support data-driven processes with AI.

• Target Group: Doctoral candidates with proficiency in Python or R.

• Goal: To develop tailored, automated analysis workflows for large datasets.

• Key Topics: Complex analysis processes, building pipelines, and controlling models.

• Speaker: Christopher Klamm is an interdisciplinary researcher and expert at the intersection of Computer Science, Political Science, and Computational Linguistics. He is currently a PhD candidate and research assistant at the University of Mannheim (Data and Web Science Group) and the Cologne Center for Comparative Politics (University of Cologne).

Organized by the Graduate Academy. If you have any questions, please reach out to Dr. Carmen Kuhn.