Generative AI Tutorial Series: Data Analysis, Quantitative Data

Generative AI Tutorial Series: "Data Analysis, Quantitative Data"
About: 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.
Instructor: Fred Feinberg, Joseph Handleman Professor, Professor of Marketing, Stephen M Ross School of Business and Professor of Statistics, College of Literature, Science, and the Arts
Link to materials: tinyurl.com/Midas2024FF
Overview: Generative AI is revolutionizing the landscape of research by enabling unprecedented levels of automation and innovation, and facilitating major breakthroughs across all research fields. In recognition of the opportunities this presents, the Michigan Institute of Data Science (MIDAS) and the College of Literature, Science, and the Arts (LSA) at the University of Michigan are co-hosting a series of tutorials on Generative AI during the Winter ’24 semester.
Visit our series page for more information: midas.umich.edu/generative-ai...
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