About this session:
In this open-ended session, we will try to get ChatGPT, Claude, and other LLMs to generate code and graphics — both classically in R and Bayesianly in Stan — for some of the most common models run in the social and physical sciences, starting with standard regression and working our way up to various nonlinear models (e.g., GAMs, GPs), time-series / panels, and discrete choices (e.g., binary and multinomial logit). The emphasis will be on data exploration, generalizing code to relax assumptions underlying more computationally simple models, and locating bottlenecks in existing code.
About the series:
Generative AI is revolutionizing the landscape of research by enabling unprecedented levels of automation and innovation, and facilitating major breakthroughs across all research fields. To leverage this, MIDAS hosts tutorials on generative AI for researchers across all disciplines at U-M. We cover topics ranging from administrative tasks, literature review and synthesis, data analysis, and writing and presentations.
If you are a U-M researcher looking to learn more about when, why, and how to integrate generative AI tools into your research, please register to join us at one of our upcoming sessions. The Fall 2024 series, co-hosted by Michigan Medicine, is open to all U-M researchers. Additionally, if you are unable to attend in person, recordings of the sessions will be available for later viewing.
No prior experience with generative AI tools is required. Participants will need to supply their own laptop for each session.