Registration is required by August 17th
Data is everywhere in our work, from survey responses and course enrollments to lab measurements, budget spreadsheets, and archival records, but turning it into insight usually requires technical skills that take years to develop. Generative AI changes this equation. With tools like Claude Code, anyone can now explore, clean, and visualize data by describing what they want in plain English.
This tutorial teaches participants how to use Claude Code as a thinking partner for data inspection. By the end of the session, attendees will have explored a real dataset, produced charts and a written report, and developed a reusable workflow they can apply to their own work the next day.
This tutorial is designed for a general Northwestern audience: faculty, postdocs, graduate students, and staff from any discipline. No coding experience is required. Participants from the humanities, social sciences, administration, and STEM fields are equally welcome.
What you will learn:
Participants will leave the workshop able to:
1. Set up and navigate Claude Code with confidence, even without a technical background.
2. Translate research or work questions into effective prompts for data exploration.
3. Inspect, clean, and summarize datasets through natural-language conversation.
4. Generate publication-quality charts and a structured data report.
5. Critically evaluate AI-generated outputs and recognize when to trust them.
6. Iterate on results to refine analyses and uncover deeper patterns.
What participants will take home:
Each participant will leave with a working Claude Code setup, a data report they built themselves, a curated set of reusable prompts for data inspection, and the confidence to apply these skills to their own work immediately.
Requirements:
A laptop (Mac, Windows or Linux), a Claude account. Sample datasets and installation instructions will be provided in advance.
Northwestern Network for Collaborative Intelligence
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