Introduction to Artificial Intelligence and Machine Learning using HCC

This workshop will give participants a hands-on introduction to using HCC resources for running Artificial intelligence (AI) and Machine Learning (ML) workflows. Participants will learn how to access and utilize GPU resources on HCC's Swan and utilize PyTorch to create and train a simple model. The participants will be introduced to the National Research Platform (NRP), a free research resource for running GPU-based AI and ML workflows.

When: Tuesday, March 25th (UNLincoln) and April 8th (UNLincoln), 12pm to 4:30pm

Where:

March 25th: UNL City Campus, Jorgensen Hall Room 251

April 8th: UNL City Campus, Jorgensen Hall Room 251

Cost: FREE!!! Space is limited.

NOTE: Registration is binding!

Workshop Level: Intermediate.

Required Prerequisites:

Familiarity with Linux and the command-line

Experience with Python

Active HCC account with DUO setup

Learning Objectives:

• GPU access on HCC resources
• Accessing GPU resources on Swan
• Accessing JupyterLab on Swan
• Running AI and ML workflows on Swan
• Using PyTorch
• GPU access on other National resources

Registration:

Attendees will need an HCC account as this workshop will feature hands-on practice.

Schedule:

12pm - 12:15pm	Setup and Support Time available for setting up accounts or troubleshooting issues prior to the day's events.
12:15pm - 1 pm	Introduction to GPU resources on HCC General introduction to GPU resources Swan offers and its usage.
1pm - 1:15pm	Break
1:15pm - 2pm	AI and ML workflows Learn about how to run AI and ML workflows on Swan.
2pm - 2:10pm	Break
2:10pm - 2:50pm	Introduction to PyTorch Learn how to run GPU PyTorch code on Swan.
2:50pm - 3pm	Break
3pm - 3:50pm	Introduction to PyTorch (cont.) Learn how to run GPU PyTorch code on Swan.
3:50pm - 4pm	Break
4pm - 4:15pm	Introduction to National Research Platform (NRP) Learn about different GPU provider.
4:15pm - 4:30pm	Open Questions Time available for questions about today's events.

Setup for Hands-On

1. Login to Swan's Open OnDemand (OOD) Portal.
2. Open a terminal in OOD. Done by opening the "Clusters" menu at the top of the screen and selecting "Swan Shell Access"
3. Change to your $WORK directory and run "git clone https://github.com/unlhcc/hcc-ai-ml-workshop-2025.git" without the quotes. Verify that the data was downloaded using the "ls" command.
4. Return the the OOD main page and start a Jupyter Lab session from the "Interactive Apps" menu using the settings in the section below.
5. Navigate to the "hcc-ai-ml-workshop-2025" directory on the left hand side of the screen.
6. Open the "prepare_datasets.ipynb" notebook and run all cells
7. When all cells have finished execution without error, put up your YELLOW sticky note.

Open OnDemand Settings:

Parameter	Value
Jupyter Lab version	4.0
Working Directory	/work/<group name>/<user name>
Number of cores	8
Running time in hours	3
Requested RAM in GBs	32
Partition selection	gpu
Reservation	Located on the back of your name tag
GRES	gpu
Job Constraints	---Leave BLANK---

Resource Reservation for GPUs: Located on back of nametags

JupyterLab Settings:

Parameter	Value
INSIDE JUPYTER LAB: Kernel Name	hcc-ai-ml-workshop-2025

Useful links and commands for the workshop:

Workshop Notebooks Repository

Intro to ML and AI Slides

ML/AI Workflows

Introduction to PyTorch

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Workshop Feedback

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Bash Cheatsheet (External)

HCC info sheet

HCC SLURM scheduler cheat sheet

Please contact us at hcc-support@unl.edu if you have questions or concerns and we will be happy to help!