This course introduces participants to the computing environment found in UH high performance computing clusters such as Opuntia, including how to prepare work-flows, submit jobs to the queuing systems, and retrieve results. Other topics covered include general HPC concepts, Opuntia’s system architecture, system access, customizing your user environment, compiling and linking codes for CPUs or GPUs, the PBS/SLURM batch scheduling system, batch job scripts, Matlab jobs, submission of serial or interactive or parallel (gpu/cpu) jobs to the batch system. 


Topics in Linux covered include user accounts, file permissions, file system navigation, the Command Line Interface (CLI), command line utility programs, file & folder manipulation, and common text editors. 


Topics covered in Shell scripting include built-in commands, control structures, file descriptors, functions, parameters & variables, and shell scripting.

Prerequisites: None


Instructor: Ishita Sharma 

Date:  25th January 2021 - 8th  March 2021

Time: Mon ,Wed 10:30 AM - 12:00 PM 

Location: Join Microsoft Teams

Capacity: 150


Please install MobaXterm on your Windows laptop.

UH Alumni Registration Fee: $250.00

Non-UH Affiliate Registration Fee: $250.00


For more information contact us at: contact@hpedsi.uh.edu 

** Non-UH affiliates and alumni registering for the HPE DSI classes MUST:

(1) complete the payment of the course fees ($250.00 per course) at least three(3) weeks before course commencement.

(2) inform HPE DSI of their interest in taking the course at least three(3) weeks before the course start date. This will allow adequate time for processing of your course access credentials before the first-class meeting.


This course will teach you a basic understanding of how to program in R. You will learn how to use the R Studio software necessary for a statistical programming environment. The course covers reading data into R, accessing R packages, writing R functions, debugging, and commenting R code. We will introduce visualization concepts in R and you will also learn how to run R code on the HPE DSI HPC clusters.

Prerequisites: None.

Intro to Linux/Cluster computing course provided by HPE DSI is recommended.


Instructor:  Ishita Sharma

Date: 25th January 2021 - 8th March 2021

Time : Mon Wed 2:30 PM to 4:00 PM

Location: Join Microsoft Teams

Capacity: 150 

Attendees who are not current UH student, staff or faculty, will need to make a payment for the course prior to its commencement using this URL https://mynsmstore.uh.edu/index.php?route=product/product&product_id=27592

UH Alumni Registration Fee: $250.00

Non-UH Affiliate Registration Fee: $250.00


For more information contact us at: contact@hpedsi.uh.edu 

** Non-UH affiliates and alumni registering for the HPE DSI classes MUST:

(1) complete the payment of the course fees ($250.00 per course) at least three(3) weeks before course commencement.

(2) inform HPE DSI of their interest in taking the course at least three(3) weeks before the course start date. This will allow adequate time for processing of your course access credentials before the first-class meeting.




Python is an easy to learn, powerful programming language. It has efficient high-level data structures that make it suitable rapid application development. Topics covered in this session will include data types, conditional and loop statements, functions, input/output, modules, classes and exceptions. Upon completion of this tutorial series, participants should be able to understand existing scientific python codes as well as write their own simple python applications. This training session also introduces participants to scientific computing extensions of python like numpy for use in high-performance computing. Using advanced python libraries like regular expressions, scipy, pandas, seaborn, scikit-learn, etc for every day scientific computing are also taught.


Prerequisites: Participants are expected to have a working knowledge of the UNIX/Linux environment or should have taken Cluster computing course from HPE-DSI dept.


Instructor: Dr. Jerry Ebalunode

Date: 26th January 2021 - 9th March 2021 

Time: Tue Thur 10:30 AM to 12:00 PM

Location: Join Microsoft Teams

Capacity: 150

Location: Online

Attendees who are not current UH student, staff or faculty, will need to make a payment for the course prior to its commencement, using this URL https://mynsmstore.uh.edu/index.php?route=product/product&product_id=27601


UH Alumni Registration Fee: $250.00

Non-UH Affiliate Registration Fee: $250.00


For more information contact us at: contact@hpedsi.uh.edu 

** Non-UH affiliates and alumni registering for the HPE DSI classes MUST:

(1) complete the payment of the course fees ($250.00 per course) at least three(3) weeks before course commencement.

(2) inform HPE DSI of their interest in taking the course at least three(3) weeks before the course start date. This will allow adequate time for processing of your course access credentials before the first-class meeting.



This tutorial will provide hands-on skills to use modern data visualization and analysis platforms, specifically the open source parallel Paraview and Tableau. Paraview is very powerful and popular in the HPC scientific and engineering research communities. In the ParaView part, we will explore representations, color-scales and their controls, data filters, how to build pipelines, multi-view & camera links using synthetic seismic data, streamline plots, plot-over-line analysis, and histograms. Also, the calculator tool, datasets & time, animations & their controls, time interpolation, camera animations, static vector field animations, and Python scripting. Finally, the course will cover how to use these tools/skills to do remote, parallel visualization using HPE DSI computer clusters. In the Tableau workshop, we will use Tableau Public to create interactive data visualizations. It will cover an overview of the program and provide hands-on experience creating basic charts and maps, as well as creating interactive web-based visualization dashboards. We will also use more advanced features in Tableau to manage data, and use calculations and parameters to make views more interactive. In the end, students will publish their visualizations to the Tableau Public web server.


Instructors: Dr. Martin Huarte-Espinosa , Wenli Gao 

Date: 26th January 2021 - 9th March 2021

Time: Tue Thur 9:00 AM - 10:30 AM

Location: Join Microsoft Teams

Capacity: 150

HPE DSI’s courses are free for UH System students from outside the Main Campus. However, these individuals must enroll in our courses at least three weeks before the courses starting date to allow for proper registration.

Attendees who are not current UH student, staff or faculty, will need to make a payment for the course prior to its commencement, using this URL https://mynsmstore.uh.edu/index.php?route=product/product&product_id=27573

UH Alumni Registration Fee: $250.00

Non-UH Affiliate Registration Fee: $250.00


For more information contact us at: contact@hpedsi.uh.edu 

** Non-UH affiliates and alumni registering for the HPE DSI classes MUST:

(1) complete the payment of the course fees ($250.00 per course) at least three(3) weeks before course commencement.

(2) inform HPE DSI of their interest in taking the course at least three(3) weeks before the course start date. This will allow adequate time for processing of your course access credentials before the first-class meeting.



This course is an introduction to the Julia programming language. Julia is the fastest modern open-source language for data science, machine learning, and scientific computing. Julia provides the functionality, ease-of-use and intuitive syntax of R, Python, Matlab, SAS or Stata combined with the speed, capacity, and performance of C, C++ or Java. Julia also provides parallel and distributed computing capabilities out of the box, and unlimited scalability with minimal effort.

Prerequisites: None.


Instructor: Dr. Jerry Ebalunode

Time: Mon Wed 01:00 PM to 02:30 PM

Date: 25th January 2021 - 8th March 2021

Location: Join Microsoft Teams

Capacity: 150

Attendees who are not current UH student, staff or faculty, will need to make a payment for the course prior to its commencement using the following link: https://mynsmstore.uh.edu/index.php?route=product/product&product_id=27595 

UH Alumni Registration Fee: $250.00

Non-UH Affiliate Registration Fee: $250.00


For more information contact us at: contact@hpedsi.uh.edu 

** Non-UH affiliates and alumni registering for the HPE DSI classes MUST:

(1) complete the payment of the course fees ($250.00 per course) at least three(3) weeks before course commencement.

(2) inform HPE DSI of their interest in taking the course at least three(3) weeks before the course start date. This will allow adequate time for processing of your course access credentials before the first-class meeting.




Today, multiple resources such as Social Media/Healthcare applications/Banking Applications so on generate a large volume of data.

The first question which comes to our mind is how to make the data useful to help society.

This course has designed to help you familiarize yourself with some of the essential steps to begin analyzing the data and discovering the patterns on the dataset.

 It will include working on some real-world datasets covering skills such as

Data scraping, data pre-processing (data importing & cleaning), data wrangling (exploratory data analysis & data structuring) and applying statistical techniques to get ready for the machine learning algorithms.

None-HPC Certificate: This pilot course will not count towards course completion requirements for the HPC-Certificate

Pre-requisites: Familiarity with Python/R/any Programming language

Recommended: Intro to Linux/Cluster computing course provided by HPE DSI


Instructor: Ishita Sharma

Date: 26th January 2021 - 9th March 2021

Time: Tues Thur 01:00 PM - 02:30 PM

LocationJoin Microsoft Teams

Capacity: 150


Attendees who are not current UH student, staff or faculty, will need to make a payment for the course prior to its commencement, using the following link:  https://mynsmstore.uh.edu/index.php?route=product/product&product_id=27602

UH Alumni Registration Fee: $250.00

Non-UH Affiliate Registration Fee: $250.00


For more information contact us at: contact@hpedsi.uh.edu 

** Non-UH affiliates and alumni registering for the HPE DSI classes MUST:

(1) complete the payment of the course fees ($250.00 per course) at least three(3) weeks before course commencement.

(2) inform HPE DSI of their interest in taking the course at least three(3) weeks before the course start date. This will allow adequate time for processing of your course access credentials before the first-class meeting.



C++ is one of the most widely used programming languages, particularly in the STEM fields. Various C++ compilers are available for the majority of computer architectures and operating systems. This tutorial will provide skills to understand and write C++ code starting with the basics. There will be many hands-on time sessions to write code. You will learn how to write, compile and debug some C code comfortably. You will understand and use the basic con-structs of C++; manipulate C++ datatypes, such as arrays, strings, containers, and pointers; isolate and fix common errors in C++ programs; use memory appropriately, including proper allocation/deallocation procedures; apply object-oriented approaches to software problems in C++, making use of structs, classes and objects. Several C++ problems will be presented and solved. Some of the newest feature of C++ will also mentioned/looked at. 

Prerequisites: Participants are expected to have familiarity with a low level programming language such as C/C++, or Fortran, and working comfortably in a UNIX/Linux environment.


Instructor: Dr. Jerry Ebalunode

Dates: 10th March 2021 - 21st April 2021

Time : Mon Wed 10:30 AM - 12:00 PM

Location: Join Microsoft Teams

Capacity: 150

UH Alumni Registration Fee: $250.00

Non-UH Affiliate Registration Fee: $250.00


For more information contact us at: contact@hpedsi.uh.edu 

** Non-UH affiliates and alumni registering for the HPE DSI classes MUST:

(1) complete the payment of the course fees ($250.00 per course) at least three(3) weeks before course commencement.

(2) inform HPE DSI of their interest in taking the course at least three(3) weeks before the course start date. This will allow adequate time for processing of your course access credentials before the first-class meeting.





This tutorial will provide hands-on skills to use modern data visualization and analysis platforms, specifically the open source parallel Paraview and Tableau. Paraview is very powerful and popular in the HPC scientific and engineering research communities. In the ParaView part, we will explore representations, color-scales and their controls, data filters, how to build pipelines, multi-view & camera links using synthetic seismic data, streamline plots, plot-over-line analysis, and histograms. Also, the calculator tool, datasets & time, animations & their controls, time interpolation, camera animations, static vector field animations, and Python scripting. Finally, the course will cover how to use these tools/skills to do remote, parallel visualization using HPE DSI computer clusters. In the Tableau workshop, we will use Tableau Public to create interactive data visualizations. It will cover an overview of the program and provide hands-on experience creating basic charts and maps, as well as creating interactive web-based visualization dashboards. We will also use more advanced features in Tableau to manage data, and use calculations and parameters to make views more interactive. In the end, students will publish their visualizations to the Tableau Public web server.


Instructor: Dr. Martin Huarte-Espinosa,  Wenli Gao

Date: 10th March 2021 - 21st April 2021

Time: Mon Wed 01:00 PM - 02:30 PM

Location: Join Microsoft Teams

Capacity: 150



HPE DSI’s courses are free for UH System students from outside the Main Campus. However, these individuals must enroll in our courses at least three weeks before the courses starting date to allow for proper registration.

Attendees who are not current UH student, staff or faculty, will need to make a payment for the course prior to its commencement using the following link: https://mynsmstore.uh.edu/index.php?route=product/product&product_id=27613

UH Alumni Registration Fee: $250.00

Non-UH Affiliate Registration Fee: $250.00


For more information contact us at: contact@hpedsi.uh.edu 

** Non-UH affiliates and alumni registering for the HPE DSI classes MUST:

(1) complete the payment of the course fees ($250.00 per course) at least three(3) weeks before course commencement.

(2) inform HPE DSI of their interest in taking the course at least three(3) weeks before the course start date. This will allow adequate time for processing of your course access credentials before the first-class meeting.



Machine learning is the science of developing statistical methods that quantify relationships within data. This branch of mathematics/computer science has seen an explosive growth over the past decade as our ability to store and process digital data has dramatically increased. Prediction, classification, regression, and identification are the aims of learning from data. All of these problems are routinely performed in data analytic’s.

To obtain an overview of the literature in learning-based methods and applications.

To obtain an understanding of a variety of machine learning techniques for classification, regression, and prediction.

To obtain the ability to implement and experiment with a wide range of machine learning algorithms in Python with examples.

To apply: Unsupervised and Supervised learning and clustering concepts, Dimensional reduction, Kernels and kernel-based classifiers such as SVM, and Deep Learning algorithms.

To understand and implement learning-based methods for classification of data, signals and features.

Prerequisites: Participants are expected to have a working knowledge of the UNIX/Linux environment or should have taken Cluster computing course from HPE DSI dept.


Instructor: Dr. Ioannis Konstantinidis

Dates: 10th March 2021 - 21st April 2021

Time: Mon Wed 2:30 PM to 4:00 PM

Location: Join Microsoft Teams

Capacity: 150

Attendees who are not current UH student, staff or faculty, will need to make a payment for the course prior to its commencement using this URL https://mynsmstore.uh.edu/index.php?route=product/product&product_id=27568


UH Alumni Registration Fee: $250.00

Non-UH Affiliate Registration Fee: $250.00


For more information contact us at: contact@hpedsi.uh.edu 

** Non-UH affiliates and alumni registering for the HPE DSI classes MUST:

(1) complete the payment of the course fees ($250.00 per course) at least three(3) weeks before course commencement.

(2) inform HPE DSI of their interest in taking the course at least three(3) weeks before the course start date. This will allow adequate time for processing of your course access credentials before the first-class meeting.




This course is divided into 2 main parts:
Part 1: Use of CUDA which makes it easier for specialists in parallel programming to use GPU resources
Part 2: Programming GPUs using high level programming language - MATLAB and directive based approaches including OpenACC and OpenMP (if time permits)

Prerequisites: Familiarity with a low level programming language such as C/C++, or Fortran, Matlab and working comfortably in a UNIX/Linux environment or completed corresponding HPEDSI courses (cluster computing, C++).
Note for HPC certificate – you should have completed the linux/cluster computing

Instructor: Dr. Jerry Ebalunode

Date: 11th March 2021 - 22nd April 2021

Time: Tues Thur 10:30 AM - 12:00 PM

Location: Join Microsoft Teams

Capacity: 150


UH Alumni Registration Fee: $250.00

Non-UH Affiliate Registration Fee: $250.00


For more information contact us at: contact@hpedsi.uh.edu 

** Non-UH affiliates and alumni registering for the HPE DSI classes MUST:

(1) complete the payment of the course fees ($250.00 per course) at least three(3) weeks before course commencement.

(2) inform HPE DSI of their interest in taking the course at least three(3) weeks before the course start date. This will allow adequate time for processing of your course access credentials before the first-class meeting.