In this conversation, Mine Çetinkaya-Rundel, data science educator at Duke University and Posit, joins Michael, Hadley, and Wes to talk about teaching data science in a time when AI can write the code for you. Mine shares her journey from actuarial science to academia, the teaching philosophy behind the “whole game” approach, and her experiments using LLMs for instant student feedback. Along the way, the group dives into the joys and risks of coding by hand, the role of open source in the classroom, and what it’s like to work across both the R and Python communities.
What’s Inside:
- How a career in actuarial science led Mine to the world of data science and teaching
- The “whole game” approach to learning and how it helps students stay motivated
- Building an LLM-powered feedback tool for low-stakes assignments
- Balancing AI assistance with the need for hands-on coding experience
- The shared DNA of R and Python scientific computing communities
- The hidden value of live coding, pair programming, and seeing the process — not just the output
