Foundations of AI: Intro to Generative AI for Coders - Accelerated
2026-05-14 15:00 - 17:00 (America/New_York) | via Zoom
This will be an accelerated version of our popular “Intro to Generative AI” course, intended to give an overview of what Generative AI is, how it works from a high level, and how to use basic technical tools to leverage Generative AI.
Those who take this course will have the basic knowledge needed to use LLMs to create useful tools, and will have the understanding behind the technology to improve their prompt engineering skills as well.
This course is ideal for people who are interested in the Advanced Generative AI for Coders and Deep Dive into Retrieval Augmented Generation courses but have not taken classes in the technical basics of generative AI.
Prerequisites: Intermediate Python, some familiarity with AI/Machine Learning is helpful but not required.
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Scholarship Information
NCDS is pleased to offer a limited number of full scholarships to faculty, staff, and students affiliated with nonprofit higher education institutions.

To apply for a full scholarship, complete this Google form.
DO NOT complete the UNC Event Registration form unless you are asked to complete it.
Scholarship Recipients will be notified no later than Friday, May 1, 2026.

Foundations of AI: Advanced Generative AI for Coders
2026-05-21 13:00 - 17:00
This new course will introduce more advanced topics in Generative AI, including a deeper look at some of the tools we touch on in the intro course as well as introducing new topics like agentic AI and the broader aspects of a modern AI workflow. We’ll go over deterministic workflows versus autonomous agents, advanced prompting, schema-constrained outputs, and more to take your generative AI knowledge to the next level and help you get the most out of the power of Generative AI as a coder. After taking this course, you should be able to use and understand Generative AI beyond its use in chatbots. It is strongly recommended to have some knowledge of generative AI, NLP, and Python before taking this course.
Prerequisites: Intermediate Python skills and a basic understanding of generative AI – if you do not have any background in generative AI, you are encouraged to register for the accelerated Intro to Generative AI class offered before this course to get up to speed on the basics.
Register for the Event
Scholarship Information
NCDS is pleased to offer a limited number of full scholarships to faculty, staff, and students affiliated with nonprofit higher education institutions.

To apply for a full scholarship, complete this Google form.
DO NOT complete the UNC Event Registration form unless our staff asks you to complete it.
Scholarship Recipients will be notified no later than Friday, May 1, 2026.

Foundations of AI: Deep Dive into Retrieval Augmented Generation (RAG)
2026-05-28 15:00 - 17:00
This brief course will take what we’ve learned in the Intro to Generative AI (or Accelerated GenAI) course and go deeper in the world of Retrieval Augmented Generation (RAG) systems. You’ll learn to upgrade your RAG with query rewriting, reranking, citation generation, and more sophisticated evaluation tools. We’ll also touch on agentic RAG. You should come out of this class with the tools to make a more sophisticated RAG system. It is strongly suggested to have knowledge of Generative AI and Python coding, NLP is useful but not required.
Prerequisites: Intermediate Python skills, knowledge of generative AI may be useful but is not required.
Register for the Event
Scholarship Information
NCDS is pleased to offer a limited number of full scholarships to faculty, staff, and students affiliated with nonprofit higher education institutions.

To apply for a full scholarship, complete this Google form.
DO NOT complete the UNC Event Registration form unless our staff asks you to complete it.
Scholarship Recipients will be notified no later than Friday, May 1, 2026.

DataBytes: AI-Powered Development for Research Cyberinfrastructure
2026-06-23 12:00 - 13:00
AI coding assistants are reshaping how research software is built and maintained, but most guidance targets industry, not research cyberinfrastructure (CI).
During this webinar, Komal Thareja, a Senior Research Software Engineer at RENCI at the University of North Carolina at Chapel Hill, will fill that gap with hands-on demonstrations tailored to CI roles, using real examples from NSF Major Facility projects. Topics include scaffolding scientific workflows, generating APIs from OpenAPI specs, building publication dashboards, and creating presentation materials. Designed for PIs/managers, developers, and students, the session highlights workflows you can adopt immediately, common AI failure modes, prompt techniques that improve results, and security considerations for using AI with research code. No prior AI experience required.
Key Takeaways for attendees:

Role-specific AI workflows for research CI, drawn from real NSF Major Facility projects
Practical guidance for PIs/managers, developers, and students
What AI gets wrong in research software—and how to recover
Prompt engineering techniques that improve scientific software outcomes
Security best practices for using AI with research code and infrastructure

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