GRAD 778 - Elements of Research Computing

We are pleased to announce the return of an exciting opportunity for graduate students, postdocs and faculty to acquire and/or improve their skills in research computing.

Course overview

Instructors from across campus will be offering an intensive module-based course that will be an overview of computational research as well as a skills-based introduction to programming and shell scripting for automating computational tasks.  Lectures will be made available via prerecorded video, followed by real-time live discussions, demonstrations, and exercises on Saturdays from 9am to 12pm during the Fall semester. Students can select from mini-courses of interest and “build their own curriculum,” choosing which weekend modules work with their interests and schedule.

Course topics

  • Introduction to Linux
  • Introduction to R (Part 1)
  • Data Operations and Programming in R (Part 2)
  • Documentation and reproducibility
  • C++ Programming 1- Dynamic and Parallel Programming
  • C++ Programming 2- Computer Vision
  • Introduction to Python
  • Version Control
  • Batch Processing on Pronghorn
  • Singularity Containers

Anyone interested in using computational tools for research is encouraged to attend, including graduate students, postdocs, faculty, and staff. Attendees will have the opportunity to work hands-on with various real-world examples and write basic programs in more than one programming language. Modules will be part pre-recorded video lecture, part open discussion, and part hands-on practice. Each module is held in mini-session format in which lessons will be fully inclusive within each weekend module, with the exception of R and C++ in which module curriculum extends over two weekends (Part 1 and Part 2).  Attendees must have their own laptop and a valid NetID.  

The graduate version of the course, GRAD 778, Elements of Research Computing is cross listed in several departments (including Biology, CSE, NRES, and Psychology) and is available for registration in MyNevada.

Students intending to register for graduate-level S/U credits will have the option of attending:

  • 3 modules = 1 credit
  • 6 modules = 2 credits
  • 9 modules = 3 credits

The course will be capped at 80 students, but we will allow auditing of the course by faculty, staff, and students if there are available (virtual) seats.

Interested students or auditors will be required to attend the mandatory course introductory session via Zoom on Saturday, August 29th at 9am. For more information, please contact Jonathan Greenberg at jgreenberg@unr.edu.