Hands-On AI for Research: Practical Tools to Accelerate Your Work

A Five-Part Training Series for CCTSI Researchers

Artificial intelligence tools are rapidly becoming part of the day-to-day research workflow, yet many of us lack practical guidance on how to use them effectively and responsibly. This hands-on training series focuses on concrete, real-world applications of AI that directly support research without requiring prior technical expertise. No prior AI, coding, or data science experience required to participate.

Across five topics, participants will learn how to apply modern AI tools to common tasks such as literature synthesis, presentation creation, document parsing, and workflow automation. The emphasis is on using AI to accelerate work while remaining grounded in authoritative sources, institutional tools, and human judgment.

Sessions are designed to be practical, collaborative, and immediately useful, with participants encouraged to bring examples from their own work. 

Choose the workshop(s) that interest you most. Each is an in-person, standalone, two-session module, and participants should plan to attend both sessions.

A registration link will be posted here once registration opens.

Format & Structure

Each topic is delivered as an in-person, two-session module to support both learning and application.

Session 1: Guided Demo + Hands-On Practice (1 hour)
Each module begins with a short demonstration of the tool or workflow, followed by time for participants to replicate the example on their own laptops. The goal is to ensure everyone leaves with a working baseline they can adapt to their own needs.

Session 2: Troubleshooting + Low-Pressure Show & Tell (1 hour)
The second session starts with a review of common questions or issues, with members of the Kalpathy-Cramer lab serving as "teaching assistants". Participants are then invited (but not required) to share what they tried, whether it worked perfectly, partially, or not at all. This informal “show and tell” is meant to surface real-world use cases, lessons learned, and practical tips in a supportive, judgment-free environment.

Participants are encouraged to experiment between sessions and to bring examples, questions, or ideas rather than polished results.

Course Topics

Workshop Dates

What You Need

• A laptop (Mac or Windows)
• A Google account (CU-affiliated account strongly preferred)
• A CU Microsoft account for Copilot-based sessions
• Sample materials you are comfortable working with (e.g., PDFs, outlines, biosketch content)
• No prior AI, coding, or data science experience required