Cyberinfrastructure Technology Integration

Clemson Computing and Information Technology (CCIT) provides research cyberinfrastructure resources and advanced research computing capabilities through its Cyberinfrastructure Technology Integration (CITI) group.

Training Workshops

CITI partners with researchers across campus and across the country to offer a diverse catalog of advanced computing training opportunities for Clemson University students, researchers, faculty, and staff, as well as opportunities for our external partners at other universities and organizations. If you have problems with or questions about course registration, please email ithelp@clemson.edu with the words “Palmetto training” in the subject.

All workshops listed below are free for Clemson University students, faculty and staff. Registration is required, and can be done at https://cucourse.app.clemson.edu/it-training/student-index.php one week prior to the listed start dates.

Fall 2019 Schedule of Workshops

Introduction to Linux

Introduction to the Linux Command Line Interface for researchers

Location: Main Campus (Clemson)

  • Tuesday, Aug 27, 1:00PM - 4:00PM. Building/Room: Cooper Library/Room 406A
  • Tuesday, Sep 24, 9:00AM - 12:00PM. Building/Room: TBD
  • Monday, Oct 21, 9:00AM - 12:00PM. Building/Room: TBD

Location: Zucker Family Graduate Education Center (North Charleston)

  • TBD

Introduction to Research Computing on Palmetto Cluster

This workshop introduces participants to the Palmetto Cluster–Clemson University’s largest high-performance computing resource–its structure and basic usage and how to submit computational tasks to the cluster.

Location: Main Campus (Clemson)

  • Wedsnesday, Aug 28, 1:00PM - 4:00PM Building/Room: Cooper Library/Room 406A
  • Thursday, Sep 26, 9:00AM - 12:00PM. Building/Room: TBD
  • Wednesday, Oct 23, 1:00PM - 4:00PM. Building/Room: TBD

Location: Zucker Family Graduate Education Center (North Charleston)

  • TBD

Introduction to Programming in Python

This workshop introduces participants to programming, using the Python programming language, and is built around common scientific tasks such as loading, analyzing and visualizing data. The intended audience is researchers or students with no prior programming experience.

Location: Main Campus (Clemson)

  • Tuesday, Sep 10, 12:00PM - 3:00PM. Building/Room: Cooper Library/Room 406A
  • Friday, Sep 13, 9:00AM - 12:00PM. Building/Room: Cooper Library/Room 406A

  • Wednesday, Oct 16, 1:00PM - 4:00PM. Building/Room: TBD
  • Friday, Oct 18, 1:00PM - 4:00PM. Building/Room: TBD

Introduction to Hadoop on the Cypress Cluster

This workshop introduces participants to the Hadoop ecosystem and the Cypress Cluster–Clemson University’s largest Hadoop cluster. The Cypress Cluster is housed, networked, and integrated with Clemson’s Palmetto Cluster. This workshop will cover Hadoop’s architecture, the Cypress Cluster’s structure, import and export of big-data, basic usage, and how to submit scalable data analysis jobs to the Cypress Cluster. This workshop will incorporate the use of JupyterHub and Jupyter “Notebooks”. An understanding of the Linux command line and some Python experience would be beneficial (see other CITI trainings).

Location: Main Campus (Clemson) - NOTE: These main-campus sessions may be broadcast from Charleston to Clemson with in-person facilitation at Clemson or a recording of the Charleston session will be made available.

Location: Zucker Family Graduate Education Center (North Charleston)

Introduction to Big Data Analytics in Python

This workshop will teach how to how to utilize Apache Spark and Python to perform large-scale, in-memory data analytics. Learning outcomes of this workshop include understanding the overall conceptual design of Spark and demonstrate the advantages of using Spark over traditional Hadoop MapReduce. Participants will also learn to develop Spark programs using Python and to leverage Spark’s specific capabilities such as SQLContext and DataFrame to assist with data analytics. Most importantly, we will teach you how to leverage Clemson University’s Cypress Cluster to run large-scale, in-memory data analytics.

NOTE: This is now an all day training. There will be a 1 hour lunch break from 12:00PM - 01:00PM. Lunch WILL NOT be provided.

Location: Main Campus (Clemson)

  • NOTE: These main-campus sessions will be broadcast from Charleston to Clemson with in-person facilitation.

Location: Zucker Family Graduate Education Center (North Charleston)

Introduction to Data Science using R

Introduction to R language for data analytics using RStudio on PC and also Jupyter notebooks on Palmetto. Workshop contents include basic understand of R, installation of additional R modules, introduction to data manipulation, introduction to visualization, and several best practices for using R. No prior knowledge of R or programming in general is required.

Location: Main Campus (Clemson)

  • Wednesday, Sep 18 1:00PM - 4:00PM. Building/Room: Cooper Library/Room 406A
  • Friday, Sep 20, 9:00AM - 12:00PM. Building/Room: Cooper Library/Room 406A

  • Monday, Nov 4, 9:00AM - 12:00PM. Building/Room: TBD
  • Thursday, Nov 7, 9:00AM - 12:00PM. Building/Room: TBD

Introduction to Machine Learning using R

Machine learning is the science of teaching computers to reproduce the assigned procedure without being explicitly programmed. It has been used in many practical applications such as self-driving cars, speech recognition, email spam classification. It has been widely used not only in engineering (hydroinformatics, bioinformatics, genomics, geosciences and remote sensing, mechatronics) but also in economy, health sciences and even in real estates industry. This workshop provides an overall introduction to machine learning specifically with R programming language which utilizes abundance of R statistical packages. Such topics include: (1) Supervised learning (regression analysis, distance-based algorithm, regularization algorithm, tree-based algorithm, Bayes algorithm, support vector machines, artificial neural networks). (2) Unsupervised learning (clustering, dimensionality reduction). The course will also draw from numerous case studies and applications that can be applied in different engineering programs.

Pre-requisite for the course is “Introduction to Data Science using R”, offered by CITI team.

Location: Main Campus (Clemson)

  • Monday, Nov 11 9:00AM - 12:00PM. Building/Room: TBD
  • Wednesday, Nov 13, 1:00PM - 4:00PM. Building/Room: TBD

Introduction to Machine Learning using Python

Location: Main Campus (Clemson)

  • Friday, Nov 15, 1:00PM - 4:00PM. Building/Room: TBD

GIS Training

For GIS Training, please visit Clemson Center for Geospatial Technologies.

Certificate

Certificate for all CITI-ACDS workshops are here: