Instructor: Connor T. Jerzak
Teaching Assistants: Gauthier Fally (2026)
Description: In an era where data and AI drive decision-making in policy, government, and social sciences, this hands-on introductory course equips students with essential programming and computational skills to analyze complex social phenomena. Students will learn foundational programming in R, SQL, and Python, as well as how to find, collect, and clean information from open data portals, APIs, and the web using AI agents. Along the way, we emphasize reproducibility (notebooks, version control), clear communication of data quality (tables, maps, and figures), and core principles behind trustworthy programming and data analysis in the AI age. A recurring theme of the course is that while today you can accomplish a great deal with one-shot prompting in general-purpose AI tools, deeper technical understanding of programming, data, and workflows unlocks qualitatively new kinds of questions you can ask and answer at scale. Through hands-on projects involving web scraping, data visualization, and designing/deploying autonomous AI agents, participants will gain practical experience to accelerate research and problem-solving.
Guest speakers including:
– Isaac Corley (Taylor Geospatial/TorchGeo) – April 14, 2026 [Video]
– Gauthier Fally (UT Austin) – March 12, 2026
– Rush Hogan (Ascendancy Strategic Partners) – March 24, 2026
– Huimin Li (Princeton) – February 17, 2026
– Joe Liang & Xiaolong Yang (Harvard) – April 21, 2026 [Video]
– SayedMorteza Malaekeh (UT Austin) – January 29, 2026
– Mahmut Yilmaz (UT Austin) – April 21, 2026
– Fucheng Warren Zhu (Harvard) – February 5, 2026
and others TBD based on availability.
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