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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

The new Computational Modeling and Analysis Core of the Center for Integrative Neuroscience is pleased to offer an intensive module-based course that will be an overview of computational research as well as a skills-based introduction to programming for automating computational tasks. Lectures are delivered in an online setting. Each workshop is designed to run approximately three hours on Saturday mornings. Please see below a tentative schedule of workshops. Students can select from mini-courses of interest and “build their own curriculum,” choosing which weekend modules work with their interests and schedule. Workshops are generally designed with minimal pre-requisite knowledge about each unit. 

Course topics

• Documentation and Communication (Overleaf): 3 hours instructional - design, write, maintain and disseminate research results
• Intro to Linux: 3 hours instructional - shell programming for Linux environments
• Python: 9 hours instructional- 3 x 3-hour modules - introductory, intermediate and advanced programming in Python
• Introduction to Deep Learning: 3 hours instructional - Deep learning and main foundational architectures for science and engineering
• Classification with Deep Learning: 3 hours instructional - Using deep architectures to perform classification tasks
• Segmentation with Deep Learning: 3 hours instructional - Using deep architectures to perform segmentation tasks
• Large Language Models (ChatGPT): 3 hours instructional - The recent advances in large language models and how to use LLM-based AI tools in research
• Statistics I: 3 hours instructional - Introduction to power analysis, statistical tools and analytics
• Statistics II: 3 hours instructional - Advanced statistical tools and analytics

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. Each module is held in mini-session format in which lessons will be fully inclusive within each weekend module. Attendees must have 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 MyÁùºÏ±¦µä. 

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

Interested students or auditors will be required to attend the mandatory course introductory session via Zoom on Saturday, January 25 at 10 a.m. at the Zoom link below:

Link: TBA

For more information, please contact Alireza Tavakkoli (tavakkol@unr.edu).