Tuesdays, October 1 - November 12, 2024
3:00-4:30 p.m. CT

The ability of artificial intelligence (AI) to successfully learn from large datasets has transformed science and engineering as we know it. AI can accelerate scientific discovery and innovation but often requires more computing power than is available to most researchers. The DOE provides supercomputers to solve the nation’s biggest scientific challenges and this series aims to introduce a new generation of AI practitioners to these powerful resources.

Building on the ALCF's robust training program in the areas of AI and supercomputing, we are hosting a series of hands-on courses that will teach attendees to use leading-edge supercomputers to develop and apply AI solutions for the world's most challenging problems. This year, we will focus on understanding the fundamentals of large-language models (LLMs) and their scientific applications. 

Pre-requisites

This training series is aimed at undergraduate and graduate students enrolled at U.S. universities and community colleges. Attendees are expected to have basic experience with Python. No supercomputing or AI knowledge is required.

Workshop Series Format

Each session will have both lecture and hands-on components, along with a talk from an Argonne scientist about the work they do using AI for their science.

Each session occurs on Tuesdays from 3:00-4:30 p.m. CT. Session recordings will be made available shortly after each event.

Attendees who complete all in-class and post-class exercises by the end of the series will receive a certificate of completion and a digital badge.

Session materials are hosted on the ALCF AI Science Training series GitHub [click here].

Recordings for each session will be posted weekly on the session-specific pages below.

Registration 

The deadline to register is September 29, 2024. The series is free to attend, but registration is required. Attendees will receive the link to the webinar once they have registered.

Please register if you are able to commit to attend all 7 sessions. For those who cannot commit to all sessions, materials and session recordings will be made publicly available after each session. Registration restrictions may be enforced at our discretion.

To register, please visit here.