From Prompt to Pipeline: Using AI in Quantitative Research

About

AI is transforming how social scientists design, collect, and analyze data. Large Language Models (LLMs) now function as powerful “digital research assistants,” but using them effectively requires more than just prompting: it demands careful attention to efficiency, ethics, and transparency. This hands-on course equips participants with the skills to integrate AI confidently into their quantitative research workflows. Together, we move step by step through the research pipeline—literature review, research design, data collection, and data processing—exploring at each stage how AI can support, accelerate, or even reshape familiar practices. Participants will experiment with accessible AI tools, critically assess their benefits, risks, and limitations, and learn strategies to avoid common pitfalls. With AI evolving rapidly, the focus is not only on current best practices but also on developing adaptable, open-science workflows that will remain valuable as new tools emerge.

Course leader

Marco Steenbergen - University of Zurich

Target group

Professionals, researchers and students who wish to develop high-quality surveys and employ up-to-date statistical methods for survey and quantitative data analyses. Potential attendees include survey practitioners, marketing professionals, social science students, and researchers.

Fee info

Fee 700 EUR, for professionals