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Education and Training Program

An extensive educational and training program in research computing is available on campus led by PICSciE and co-sponsored or supported by key campus partners including the Center for Statistics & Machine Learning, Program in Applied and Computational Mathematics (PACM), the Princeton Neuroscience Institute, OIT Research Computing and various academic departments. The program includes:

Workshops & Live Training

Princeton Research Computing offers a number of workshops each semester on topics related to programming and commonly used research software. Programming topics focus on using Python, and writing parallel programs in C, C++ and Fortran. Other topics include the Globus data transfer tool, visualization, and version control.

Graduate Certificate in Computational Science and Engineering

Scientific computation requires a working knowledge of numerical analysis, best-practices in software engineering, computer science, and statistics and data modelling. The graduate certificate in computational and information science is open to currently enrolled Princeton University graduate students. It is designed to recognize the achievements of students who have undertaken comprehensive training in these topics, both through formal course work and through research in their subject area.

Archives of Past Workshops

Materials and/or recordings of past workshops (when available) can be accessed from this page.

User Groups

Information about the Python, TensorFlow & PyTorch and MATLAB user groups.

Online Tutorials

Research Computing provides a variety of tutorials to help researchers get started using our systems. These cover getting access, compiling and running programs, using the SLURM scheduler, GIS software, and using Map/Reduce and Spark. Links are also provided to many other tutorials on programming and on using common software packages.

Fall 2023 Workshop Materials
Workshop Date  Time Instructor(s) Introduction to Programming Using Python (Section I) [GitHub repo] 9/11, 9/12, 9/14 4:30-6:00PM Matthew Cahn Managing Research Data [

Training

High-Performance Python for GPUs
Location
View location on My PrincetonU
Data Visualization in Python
Location
View location on My PrincetonU

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