This list includes all courses offered by CRC throughout the year. To view upcoming courses and registration information, visit Registration. To download presentation, lecture slides, labs, and other materials from recent courses, log into your Box account.
Pitt CRC Spring Workshops
Cluster Training: Thursday Jan. 24, 1-4 pm. Location: 311A Schenley Place.
Our semi-annual cluster training workshop presented by Pitt CRC consultant Shervin Sammak. We will go over the new hardware and modules, and the queuing system that is in production. We will present some useful concepts for computations using SLURM, including queuing many small jobs as one job, using the scratch space, and trapping exit codes for restarts.
Practical Everyday Linux: tools and tricks for maximizing your utilization of HPC resources. Wednesday, Feb. 20, 1-4 pm. Location: 311A Schenley Place.
This workshop presented by Pitt CRC consultant Kim Wong is a followup to the Cluster Training Workshop and will provide hands-on experience with intermediate Linux commands, Linux environment settings, and bash scripting examples that will make your computational research projects more efficient, more organized, and more enjoyable. Prerequisite: must have completed the Cluster Training Workshop or have previous experience with the Linux command line and text editing.
R for Genomics. Thursday March 21, 1-4 pm. Location: Health Sciences Library System Conference Room B.
This workshop presented by Pitt CRC consultant Fangping Mu will introduce the R and Bioconductor environment on the HTC cluster. The hands-on session will use Rstudio server on Open Ondemand.
Introduction to Data Science with R. Wednesday, April 17, 1-4 pm. Location: 311A Schenley Place.
This workshop presented by Pitt CRC consultant Kim Wong will introduce attendees to tools for performing data science with R. We will cover three essential skill sets of data science: data wrangling (data loading, cleaning, and manipulation to enable downstream computation), programming with R, and modeling using statistical methods. Prerequisite: Introductory-level experience using R.
Basic Coding and Machine Learning with MATLAB: Tuesday, April 22, 1-4 pm. Location TBD.
In this workshop, we will explore ways to leverage MATLAB for basic computations, followed by discussion of different types of machine learning techniques and their workflows. The workshop will conclude with hands-on activity with real data using MATLAB Statistics and Machine Learning Toolbox. The presenter will be Elvira Osuna-Highley, PhD, senior customer success engineer at MathWorks, Inc
Register for all workshops at https://crc.pitt.edu/spring19workshop.
If you need a CRC account, apply for one at http://crc.pitt.edu/apply.