Research Computing Trainings & Video Library

Upcoming Research Computing Workshops

San Diego Supercomputer Center
June 11 | Containers (COMPLECS)

Free and open to CU! COMPLECS (COMPrehensive Learning for end-users to Effectively utilize CyberinfraStructure) is a SDSC training program that covers the most important non-programming concepts and skills needed to effectively use supercomputers.

San Diego Supercomputer Center
July 9 | Intermediate Linux (COMPLECS)

Free and open to CU! COMPLECS (COMPrehensive Learning for end-users to Effectively utilize CyberinfraStructure) is a SDSC training program that covers the most important non-programming concepts and skills needed to effectively use supercomputers.

San Diego Supercomputer Center
August 20 | Getting Started with Batch Job Scheduling (Part II) (COMPLECS)

Batch Job Scheduling Part 1

Free and open to CU! COMPLECS (COMPrehensive Learning for end-users to Effectively utilize CyberinfraStructure) is a SDSC training program that covers the most important non-programming concepts and skills needed to effectively use supercomputers.

San Diego Supercomputer Center
September 3 | Linux tools for text processing (COMPLECS)

Free and open to CU! COMPLECS (COMPrehensive Learning for end-users to Effectively utilize CyberinfraStructure) is a SDSC training program that covers the most important non-programming concepts and skills needed to effectively use supercomputers.

Our colleagues from Research Data Services at the Columbia Libraries also offer on-demand workshops and class visits on applications for a range of popular tools, including R, Stata, Git.

RCS/HPC Video Library

Check out past sessions!

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Peer Institute & Industry Events/Resources

RCS maintains relationships with our vendor partners and peer institutions to help support research and education, including fellow Ivys and R1 Universities, Intel, NVIDIA, AWS, Globus, SnapGene, GraphPad Prism and more. Let us know if you want us to look into arranging a webinar on a specific topic for our Columbia users!

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On-demand: MATLAB Self-paced Online Courses

Columbia's MATLAB subscription includes free access to MathWorks' self-paced online courses. Some options include:

  • MATLAB Fundamentals provides a comprehensive introduction to standard features.
  • Computational math courses use MATLAB to combine math applications with computing technologies.
  • Deep learning  
  • Machine learning
  • Data visualization

Course certificates are available upon completion!

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NVIDIA Developer Program

Join for free software, technical documentation, learning resources, plus peer and domain expert help.

Other key NVIDIA resources

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Free Higher Education GCP Classes

Recommended Online Tutorials

National Student Data Corps Video Library

Watch videos on data science topics based on IBM’s OpenDS4All curriculum, as well as student-created SQL and R educational materials, data science use cases, and more, presented by data enthusiasts from around the world

Cornell Virtual Workshops

Cornell has pioneered an intuitive learning platform with trainings on programming languages (e.g. Python, R, MATLAB), parallel computing, code optimization, and data analysis. The platform supports learning communities around the world, with code examples from national systems such as FronteraStampede2, and Jetstream2.

Data Science Resource Repository (DSSR)

Curated set of 1,300+ resources for learners, educators, researchers, career explorers, and professionals that promotes data science literacy.

The Missing Semester of Your CS Education

In 2020, MIT instructors put together a course curriculum to bring students up to speed on "computing ecosystem literacy" to help fill the gaps between the advanced topic instruction that Computer Science students often receive. Topics include Shell Tools and Scripting, Version Control (Git), Debugging and Profiling and more. There also are community translations in 15 languages.

Python Tutorials for Digital Humanities

Short, digestible YouTube videos (under 15-minutes) focused on teaching Python applications that are useful to non-STEM academics, such as NLP techniques (text analysis, named entity recognition, SpaCy), and leveraging JSON files.