MS-CC AI Readiness

This session provides a practical introduction to artificial intelligence in the context of research and higher education. Rather than focusing on theory alone, it highlights how AI is already being used across academic and administrative workflows.

Participants will:

• Understand key AI concepts and how they apply to real-world use cases
• Learn the differences between AI, machine learning, and large language models
• Identify 2 to 3 potential areas where AI could support their own work

This session establishes a shared baseline and sets the foundation for applying AI in meaningful, practical ways.

Speakers:

• Amanda Tan, Associate Director for Research Development, MS-CC
• Pavan Nara, AI Technical Specialist, MS-CC

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This session focuses on practical, immediately usable AI workflows for faculty, instructional staff, and administrators. Participants will explore widely available AI tools and learn how to apply them to tasks such as writing, literature review, teaching preparation, and communication.

Participants will:

• Explore real-world use cases and example workflows
• Learn prompting fundamentals and data handling considerations
• Leave with at least one workflow they can test immediately

This session is designed to demonstrate tangible value and build momentum for deeper adoption.

Speakers:

• Amanda Tan, Associate Director for Research Development, MS-CC
• Pavan Nara, AI Technical Specialist, MS-CC

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This hands-on session introduces participants to basic AI workflows using Jupyter Notebooks and pre-built materials. It is designed for those ready to move beyond tools and begin experimenting with simple AI models and datasets.

Participants will:

• Learn the basics of working with notebooks
• Run a simple end-to-end AI workflow

• Understand next steps for deeper technical engagement

This session serves as a bridge into more advanced MS-CC programs, including the AI Accelerator, hackathons, and technical consulting.

Speakers:

• Amanda Tan, Associate Director for Research Development, MS-CC
• Pavan Nara, AI Technical Specialist, MS-CC

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View the Presentation Slides 

Training today’s students on the wide array of AI topics is paramount to their future success. If you’re an instructor or teaching assistant looking to incorporate AI concepts or data science into your curriculum, Jetstream2 provides cloud-based, no-cost resources to help broaden your and your students’ access to powerful computing resources. Whether your goal is to host interactive Jupyter notebooks to train machine learning models or integrate Large Language Models into your workflows, we aim to provide equitable and easy-to-use access to powerful GPUs for your computational AI needs.

This session addresses the practical realities of using AI responsibly within institutional environments. Participants will explore key considerations around data sensitivity, compliance, and governance.

Participants will:

• Understand FERPA, IRB, and data sensitivity considerations
• Identify risks related to bias, transparency, and misuse
• Develop a basic checklist for responsible AI use within their institution

This session helps ensure that AI adoption is both effective and aligned with institutional policies and requirements.

Speakers: TBD

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Date: September 30, 2026
Time: 2:30pm ET

Chatbot, Workflow, or Agent?

Choosing the Right AI Architecture for Research

Build AI systems. More importantly, learn when not to.

AI agents are everywhere. But what actually makes something an AI agent? And when is an agent genuinely useful instead of unnecessarily complicated?

In this 3.5-hour hands-on virtual workshop, you’ll use practical research examples to explore how chatbots, workflows, and AI agents differ, then progressively build a simple research assistant in Google Colab.

Rather than focusing on a particular framework or vendor, you’ll learn the fundamental concepts behind modern AI systems and how to decide which approach is right for the problem you’re trying to solve.

What You’ll Learn

By the end of the workshop, you will be able to:

• Distinguish between chatbots, workflows, and AI agents
• Understand how tools extend AI capabilities
• Build a simple tool-using AI system
• Use document retrieval to ground AI responses
• Recognize where verification and human oversight are needed
• Identify research and administrative problems where agents add value

What You’ll Build

Using guided Google Colab notebooks, you’ll progressively build a simple research assistant.

Notebook 1: Chatbot vs. Workflow vs. Agent
Learn the key difference: who decides what happens next?

Notebook 2: Giving AI Systems Tools
Explore how AI systems select and use tools to complete tasks.

Notebook 3: Building a Research Assistant
Combine planning and document retrieval to produce a research briefing with verifiable citations.

Going Further: Memory and Human Oversight
An optional fourth notebook explores memory, task state, and human oversight for participants who want to continue learning after the workshop.

Who Should Attend?

This workshop is designed for faculty, researchers, research software engineers, research computing professionals, graduate students, and higher education staff interested in understanding how modern AI systems work and where they can be useful.

No previous experience with AI agents is required. Basic Python familiarity is helpful but not necessary.

No API Key Required

All core exercises run in Google Colab using a scripted mock mode, so no paid AI account or API key is required.

Participants will leave with reusable notebooks and example code, a practical framework for choosing between chatbots, workflows, and agents, and a certificate of completion from the MS-CC Agentic AI Virtual Workshop.

Speakers:

• Amanda Tan, Associate Director for Research Development, MS-CC
• Pavan Nara, AI Technical Specialist, MS-CC

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