This workshop will provide a general introduction to the MATLAB environment. Topics include the basic components of the MATLAB interface (editor, terminal, workspace, directory, etc.), variables, matrix operations, file operations, making plots, working with functions, and environment settings.

Target audience: Researchers that are…

This workshop will get participants started in data analysis using R/RStudio. It will briefly cover different components of data analysis and connect them with the goal of extracting meaning from data. We will go over an example to illustrate the data analysis process from beginning to end.

Workshop format: Presentation and hands-on…

Note: When you register for Part 1 on 9/18 you are automatically registered for parts 2 and 3 on 9/19 and 9/23. This is a 3-part workshop.

This mini-course is an introduction to Python for those with little or no programming experience. Python is a programming language used for a wide variety of applications including scientific…

In recent years, the differences between working on a personal computer and a remote machine have become increasingly blurred - and very much to our benefit!

In this workshop, we will explore the setup, configuration, and efficient use of Microsoft's Visual Studio Code (VS Code) as it relates to working on Princeton's Research…

Are you tired of Duo? Do you waste time entering your password every time you log in or do a file transfer? Do you want to automate repetitive tasks? This workshop shows participants how to remove much of the tedium that arises while performing computational research. Learn about suppressing Duo, password-less logins, aliases and shell functions,…

This workshop provides an introduction to machine learning using Python. Participants will use Scikit-Learn, Pandas and Matplotlib to solve machine learning problems using supervised learning techniques.

Workshop format: Presentation with hands-on exercises.

Target audience: This workshop is for those with no…

This workshop provides an introduction to data visualization in Python. The training focuses on three plotting packages: Matplotlib, Seaborn, and if time allows, Plotly. Examples may include simple static 1D plots, 2D contour maps, heat maps, violin plots, and box plots. The session may also touch on more advanced interactive plots.

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This session will provide a comprehensive overview of the main components of NVIDIA’s robotics stack: the NVIDIA Isaac platform for GPU accelerated robot development. Attendees will be introduced to:

Isaac Sim, a reference application for designing, simulating, testing, and training robots in a virtual environment;

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Register by joining the listserv:
https://researchcomputing.princeton.edu/learn/user-groups/gpu

GPU User Group
Friday, September 27, 2024 at 3:00-4:00 PM
Lewis Library 245

Agenda:

Updates on new hardware and developments in the field. Presentation on GPU metrics for running jobs on…

This workshop will introduce participants to deep learning using PyTorch. Learn the basic elements of a PyTorch script and see how to train a simple model using the MNIST hand-written digits dataset.

Workshop format: Presentation and hands-on

Target audience: Researchers and students interested in using PyTorch for…