An AI Bootcamp for Cyberinfrastructure Professionals

There is a critical need for a Cyberinfrastructure (CI) workforce with expertise in AI and the supporting CI technologies. This project will pilot an AI bootcamp for CI professionals with our intial offering starting in March 2022.

We are enthusiastic about the great response from the community to our Call for Participation! The Spring 2022 Bootcamp is now full, but we encourage you to still signup if you are interested. We will put you on a mailing list for early access to signups for our next bootcamp offering.

Call for Participation: An AI Bootcamp for CI Professionals – Common Foundation

Are researchers from new and interesting disciplines approaching you about their data analysis projects? Do you struggle to provide guidance to AI users?   Are you pulling your hair out trying to make sense of the complex software stacks required to support Machine Learning/Deep Learning (ML/DL)?  Are your users asking for more GPUs, more memory and more storage to support their DL training? Are you interested in expanding the amount of ML/DL work that is done on your systems?

If you answered yes to some of these questions, consider joining our pilot AI Bootcamp for Cyberinfrastructure Professionals (CIP). You will gain expertise in AI and the supporting technologies while helping us shape a training program for the CIP community. We’ve used the facings from the CaRCC RCD Professionalization effort to customize curricula for different CIP roles.  Our inaugural bootcamp will provide a common foundation for professionals with roles in any of the facings. The AI bootcamp is being offered virtually, 2-4pm eastern Tuesdays and Wednesdays from March 22 to April 27.  AI topics will be taught by experts from the Computer Science and Engineering Department at The Ohio State University.  See our list of instructors and topics bellow.

Instructors:

Topics:

  • What is Data Science and Analysis?

  • Python Tools for Data Analysis

  • Science Case studies

  • Typical Data Types (tables, images, time series, maps and text)

  • Fundamentals of Machine Learning

  • Bayesian Modeling

  • Neural Networks

  • Machine Learning and Deep Learning Frameworks for Analysis of Large Data

  • Overview of Execution Environments

  • Parallel and Distributed DNN Training

  • Distributed Machine Learning Algorithms

  • Data Science using Dask

  • Latest Trends in High-Performance Computing Architectures

  • Challenges in Exploiting HPC Technologies for DL, ML, and Data Science

  • Open Issues and Challenges

 

All sessions will be recorded. The instruction will involve a mix of lecture, discussion, and hands on activities. Computing resources will be provided by Ohio Supercomputer Center.  We are very interested in participation and feedback from professionals from a range of institutions with varying technical backgrounds and from communities that are both well represented and underrepresented in the CI workforce to help us to develop a program that is relevant, welcoming, and accessible to everyone in our community. There is no cost for the bootcamp. Fill out the following survey by Feb 28th to sign up: AI Bootcamp for CI Professionals - Spring 22

It should take 5-10 minutes (have your calendar handy, we ask about your availability for bootcamp sessions.) 

Check back on our plans for a follow on bootcamp in fall 2022 specifically for Software and Data facing CI professionals. This project is supported in part by NSF award OAC-2118250.

Contact us if you have any questions:

Karen Tomko, ktomko@osc.edu or Kate Cahill, kcahill@osc.edu

Links

About the Project

"An Artificial Intelligence Bootcamp for Cyberinfrastructure Professionals" is a pilot project funded by the NSF Cybertraining program (Award:  OAC-2118250)

Project PI: Karent Tomko, ktomko@osc.edu

Abreviated abstract: Researchers are increasingly using AI techniques in their scientific processes. This is leading to a critical need for a Cyberinfrastructure (CI) workforce that supports HPC systems with expertise in AI techniques and underlying technology. This project will pilot an AI bootcamp for CI professionals that is targeted based on the professional’s job requirements. After attending the bootcamp CI professionals will be better equipped to provide computing and data services to AI research users. This in turn will broaden adoption and effective use of advanced CI by researchers in a wide range of disciplines and will leave an impact on science and corresponding benefits to society from their successes. The training materials developed during this project will be openly shared with the CI community so that others can use and adapt the materials for similar training activities.

This project is novel in taking a holistic approach to addressing the AI expertise gap for CI professionals. We are developing an AI Bootcamp for CI professionals with the overarching goal of increasing the confidence and effectiveness of their support of AI researchers. We leverage the CI professionalization efforts of the Campus Research Computing Consortium (CaRCC) to organize our training modules and outcomes based on the four facings (Strategy/Policy facing, Researcher facing, Software/Data facing, and Systems facing).  For this pilot we are focused on developing a comprehensive training experience for Software/Data facing CI professionals. The AI Bootcamp will be offered virtually. A 6 week foundational session targeting all of the facings will be piloted in Spring 2022, followed by an additional 6 week session for Software/Data facing CI professionals in Fall 2022.  Our project team is comprised of CI professionals, experienced in training CI users and providing CI operations, and Computer Science faculty members, experienced in offering courses in Data Analytics, AI and High Performance AI with active AI-based research programs. Drawing on extensive experience and materials in hands-on experiential learning for AI, the team is putting together a comprehensive curriculum spanning foundational AI, software frameworks, and high performance computing for AI.