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Accelerate AI Winter School

07 October 2025

The Accelerate programme for Scientific Discovery at the University of Cambridge in collaboration with CSD3 and NVIDIA, is launching its first AI Winter School, a three-day intensive programme designed specifically for undergraduate students interested in Generative Artificial Intelligence. As AI becomes integral to all research disciplines, this programme aims to equip the next generation of researchers from all academic backgrounds with foundational AI skills. The programme will bring together 30 students from diverse academic backgrounds to participate in hands-on workshops, present their own research, and network with peers and industry professionals. This hybrid conference-school format provides undergraduates with practical AI skills, research presentation experience, and connections that are typically only available to graduate students.

Undergraduate students interested in AI face significant barriers to gaining practical experience and research exposure. Most AI workshops and conferences are designed for graduate students and professionals, leaving undergraduates without access to hands-on learning opportunities or platforms to discuss their work and ideas. Additionally, many undergraduates from diverse academic backgrounds lack awareness of AI career pathways and training opportunities, particularly those from underrepresented groups.

The AI Winter School solves these problems by creating a dedicated space for undergraduate learning and networking. The programme features intensive workshops on large language models and practical AI applications, giving students hands-on experience with cutting-edge tools. Crucially, all workshops and presentations are focused on the application of AI for academic research, not for generating coursework. The programme includes structured networking opportunities, mentorship sessions, and career panels to help students understand AI pathways and build professional connections. By focusing specifically on undergraduates and maintaining small cohort sizes, the programme ensures a supportive, collaborative environment and a high level of interaction with instructors and mentors, and developing meaningful peer connections.

How it will work

Students apply through a process that considers academic background, research interests, and commitment to diversity in AI. Selected participants attend three days of programming including workshops on LLMs and practical AI tools, working with high performance compute resources, talks and panels on careers in AI, and networking sessions with graduate students, researchers, and industry professionals. The programme includes accommodation and some meals. Participants leave with practical AI skills, presentation experience, and a network of peers and mentors in the field.

FAQs

The AI Winter School will run from Tuesday January 13 until Saturday January 17.

The programme is open to third-year undergraduate students from all academic backgrounds who have an interest in AI. The content is best suited for those who have a coursework project or research idea they are interested in developing. We particularly encourage applications from students in non-traditional AI fields (humanities, social sciences, etc.) and from underrepresented groups in technology.

The programme is designed to be accessible to students from a wide range of disciplines. However, to get the most out of the hands-on sessions, basic familiarity with Python is strongly recommended. No advanced knowledge of specific AI packages or higher-level mathematics is required.

The programme includes hands-on workshops on large language models, coding with AI, and accessing high performance compute environments. Workshop content is designed for students with varying levels of AI experience.

The deadline for application will be December 1st, with applicants being notified before December 22nd.

Due to funding restrictions, the programme is only open to students who are eligible for UK 'home' fee status. This is typically based on your residency status. You can find more information about fee status eligibility on the UKCISA website.

Full attendance is required to maximise the learning and networking benefits of the intensive format.

Since sessions will not be recorded, in-person attendance is required to maximise the learning and networking benefits of the intensive format.

Please direct any enquiries to accelerate-mle@cst.cam.ac.uk