Friday Discussions

Fridays, 12:10–1:00 PM. These sessions are separate from the core lecture material — they’re for stepping back and thinking about the bigger picture: how to work, how to learn, and how to thrive as a scientist in a rapidly changing environment.


Discussions are loosely structured. There is no problem set attached. The goal is to talk about things that don’t fit neatly into a lecture — questions that matter for your career but rarely make it onto a syllabus.

Topics rotate across three themes:

How to work well as a scientist-programmer Skills and habits that compound over time: how to learn code, how to build tools that outlast any single project, how to make figures that people actually want to look at.

The changing landscape AI is reshaping what it means to do computational science. We’ll look at the evidence, examine competing views, and work out what it means for how you learn, how you do research, and what skills to invest in.

Practical workshops A few sessions are hands-on: bring your laptop and expect to produce something by the end.


Sessions

# Topic Type
D1 Coding in the Age of AI Discussion + workshop
↳ Activity: The Code Audit Take-home or in-class
D2 How Do You Actually Learn to Code? Discussion
D3 Publication-Quality Figures Workshop
D4 Build Your Own R Package Workshop

Sessions are roughly one per three weeks. Check the schedule for exact Fridays.


Note

Have a topic you want to discuss? Post in the Canvas discussion board or bring it up in class. These sessions exist because the formal curriculum can’t cover everything that matters.