Generative AI for Scholarship

Harvard Data Science Initiative (HDSI) & Faculty of Arts and Sciences (FAS)

Instructor Resources

This page is not linked from the public site. Share the direct URL only with instructors and TAs.

Quick Links

Course home page short link: https://bit.ly/3ZxtPw8 — share this with participants to get them to the site quickly.

Post-session survey: https://bit.ly/4rlIBCt — direct participants here at the end of each session.

Slide Decks

Session 1

The Basics — Slide Deck

PowerPoint slides for Session 1 workshop presentation.

Site Analytics (GoatCounter)

All pages on this site are tracked using GoatCounter, a privacy-friendly, cookie-free analytics service. It tracks page views and outbound link clicks (including "Add to Calendar" buttons and notebook downloads).

Open Analytics Dashboard

What you can see in the dashboard:

Page views: Which pages are visited most, with daily/weekly/monthly trends
Outbound clicks: Clicks on external links, including "Add to Calendar" buttons and Google Colab links
Referrers: Where visitors are coming from (direct links, email, etc.)
Browsers and devices: What platforms participants are using

Note: GoatCounter does not use cookies and does not track individual users. All data is aggregate. The dashboard is publicly readable at the URL above — no login required. To change settings, log in at genaiatfas.goatcounter.com/settings.

Per-Session Instructor Guides

Session 1

The Basics — Instructor Guide

Run-of-show, Gemini and NotebookLM demo notes, discussion questions, and teaching tips.

Session 2

The AI-Empowered Coder — Instructor Guide

Run-of-show, Colab/Jupyter teaching notes, and discussion points.

Session 3

Claude Code CLI — Instructor Guide

Run-of-show, installation troubleshooting, exercise solutions, and discussion points.

Solutions and Answer Keys

Session 3 Solutions

Thermal Exercise — Instructor Solutions

Reference solutions and walkthrough for the Rubin Observatory thermal data analysis exercise.

Generated Analysis Reports

These reports were generated by Claude Code during the thermal data analysis exercise and serve as example outputs for instructors:

Session 3 Output

Thermal Analysis Lab Notebook

Complete lab notebook with plots, statistics, and analysis of the Rubin Observatory primary mirror temperature data.

Session 3 Output

ML Sunset Temperature Prediction

Machine learning analysis for predicting sunset temperatures from observatory thermal data.