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Faculty Research Workshops
The Faculty Research Workshops series will explore how emerging technologies, including AI, can enhance research productivity and expand possibilities for academic inquiry. Access recordings, tutorials, slides, and materials from past and future workshops in one central location.
Agentic Resources
May 2026
June 2026
Introduction to Using AI Tools For Academic Research
In this session, we covered installing and configuring Claude Code, the different ways to work with it (terminal, IDE integration, GUID), pricing and Columbia's access, model selection, and the key operating modes (plan, accept edits, auto, skip-permissions). We addressed data sharing and privacy concerns. We demonstrated how to integrate Claude Code into your workflow across different programming languages (i.e. R, Stata, Python). We also discussed version control and how to utilize git with Claude.
In addition, we provided suggested "assignments" for coming prepared with your own data to execute your own research in the second session.
Takeaways: The goal was to walk out with Claude Code installed and integrated into a research workflow alongside existing tools (Stata, R, Python), with a clear sense of how to start using it for one's own research.
Who this was for: this session was primarily designed for faculty who hadn't yet integrated Claude Code into their day-to-day. Heavier users were welcome but might have found session 2 more useful. Those who skipped this introductory session were advised to make sure they were prepared to participate in the second session.
Speakers:
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Using AI For Academic Research
A hands-on introduction to Claude Code for research workflows — covering setup, model selection, and operating modes, plus how to integrate it alongside tools like R, Stata, and Python and manage your work with git.
Session 1: Introduction to Using AI Tools For Academic Research
This session introduces Claude Code — covering installation, setup, and the different ways to work with it (terminal, IDE, GUI), plus pricing and Columbia's access model. You'll learn about model selection, key operating modes (plan, accept edits, auto, skip-permissions), and how data sharing and privacy are handled. The session also shows how to integrate Claude Code into a research workflow alongside R, Stata, and Python, and how to use it with git for version control.