This course prepares participants to effectively use the University of Houston high-performance computing (HPC) environments, including clusters such as Carya and Sabine. It introduces foundational HPC concepts and develops practical skills required to work in a shared computational research environment.
Participants will learn how to prepare, execute, and manage HPC workflows, as well as how to retrieve and interpret computational results. The course also provides an overview of HPC system architecture, user access procedures, and configuration of user environments. In addition, it covers the compilation and linking of scientific codes for both CPU and GPU-based computing systems.
A significant portion of the course is dedicated to job scheduling and workload management using the SLURM batch system. Participants will develop the ability to write batch job scripts, submit and monitor jobs, and run common scientific applications on HPC systems, including MATLAB, R, Python, and NAMD.
The Linux component of the course introduces essential command-line skills required for HPC usage. Topics include user account management, file permissions, directory navigation, command-line interface (CLI) usage, system utilities, and basic file and directory operations.
Finally, the course covers shell scripting for workflow automation. Participants will learn scripting fundamentals, including built-in shell commands, variables, parameters, control structures, functions, and file descriptors.
By the end of the course, participants will be able to independently navigate HPC environments, manage computational workloads, and develop reproducible scientific computing workflows on modern HPC systems.
This course is a mandatory course of the Micro-credential in High Performance Computing. Ask about this program at contact@hpedsi.uh.edu.
Prerequisites: None.
Date: 27th May 2026 - 1st July 2026
Time: Mon Wed 10:00 AM - 11:30 AM
Instructor: Dr. Jerry Ebalunode (jebaluno@Central.UH.EDU)
Teaching Assistant: Arun Reddy Karnati (akarnat2@cougarnet.uh.edu)
Location: Online (Microsoft Teams) access code: TBA
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.
Clear Lake, Victoria, Downtown, Sugar Land or Katy campuses
Attendees who are current UHS students, staff or faculty from the Clear Lake, Victoria, Downtown, Sugar Land, or Katy campuses MUST fill in this credentials form at least three(3) weeks before the course start date. This will allow adequate time to process your course access credentials before the first class.
Current UHS (all campuses) Student, Staff, or Faculty Registration Fee: Free.
UH Alumni and Non-UH Affiliates
Attendees who are not current UHS students, staff, or faculty will need to make a payment for the course prior to its commencement.
UH Alumni Registration Fee: $250.00. See refund policy
Non-UH Affiliate Registration Fee: $250.00. See refund policy
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 using this payment link: https://store.mynsm.uh.edu/index.php?route=product/product&product_id=403&search=101+introduction+to+cluster
(2) fill in this credentials form at least three(3) weeks before the course start date. This will allow adequate time to process your course access credentials before the first class.
If you don't wish to continue participating in the course, Please use the option "Unenroll me" available at the right-hand pane on the course webpage to unenroll from the course. If you have questions e-mail us at contact@hpedsi.uh.edu
The following refund schedule applies:
More than three weeks before the start date: A cancellation fee of 10% of the total workshop cost applies.
Less than three weeks before the start date: 15% cancellation fee applies.
Less than one week before the start date: 25% cancellation fee applies.
48 hours or less before class start: No refund is available.
All deposits and payments made are non-transferable. The HPE DSI cannot provide refunds, transfer payments, or offer makeup sessions for classes a student might miss, for any reason. If the HPE DSI has to cancel a workshop, you will receive a full refund.
This course is a mandatory course of the Micro-credential in Advanced Data Science Program. Ask about this program at contact@hpedsi.uh.edu.
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: Dr. Ioannis Konstantinidis (ikonstantinidis@uh.edu)
Teaching Assistant: Sathwik Sangeetham (ssangeet@cougarnet.uh.edu)
Date: 27th May 2026 - 29th June 2026
Time: Mon Wed 2:30PM - 4:00 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 classes starting date to allow for proper registration.
Clear Lake, Victoria, Downtown, Sugar Land, or Katy campuses
Attendees who are current UHS students, staff or faculty from the Clear Lake, Victoria, Downtown, Sugar Land, or Katy campuses MUST fill in this credentials form at least three(3) weeks before the course start date. This will allow adequate time to process your course access credentials before the first class.
Current UHS (all campuses) Student, Staff or Faculty Registration Fee: Free.
UH Alumni and Non-UH Affiliates
Attendees who are not current UHS students, staff, or faculty will need to make a payment for the course prior to its commencement.
UH Alumni Registration Fee: $250.00. See refund policy
Non-UH Affiliate Registration Fee: $250.00. See refund policy
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 using this payment link : https://store.mynsm.uh.edu/index.php?route=product/product&product_id=407&search=211+r+for+data+science
(2) fill in this credentials form at least three(3) weeks before the course start date. This will allow adequate time to process your course access credentials before the first class.
If you wish to withdraw from the course, Please use the option "Unenroll me" available at the right-hand pane on the course webpage to unenroll from the course. Feel free to e-mail us at contact@hpedsi.uh.edu, if you have questions.
The following refund schedule applies:
More than three weeks before the start date: A cancellation fee of 10% of the total workshop cost applies.
Less than three weeks before the start date: 15% cancellation fee applies.
Less than one week before the start date: 25% cancellation fee applies.
48 hours or less before class start: No refund is available.
All deposits and payments made are non-transferable. The HPE DSI cannot provide refunds, transfer payments, or offer makeup sessions for classes a student might miss, for any reason. If the HPE DSI has to cancel a workshop, you will receive a full refund.
Python is a powerful, easy-to-learn programming language widely used in scientific computing, data analysis, automation, and high-performance computing (HPC). Its clear syntax, extensive standard library, and efficient high-level data structures make it well suited for rapid application development and computational research.
This training session introduces participants to the fundamentals of Python programming and its applications in scientific and research computing. Topics covered include Python syntax, core data types, conditional statements, loops, functions, file input/output, modules, object-oriented programming with classes, and exception handling.
The course also provides hands-on exposure to commonly used scientific Python libraries and tools for data processing, visualization, and computational analysis. Participants will learn to use libraries such as NumPy for numerical computing, SciPy for scientific computing workflows, Pandas for data manipulation and analysis, Seaborn for data visualization, Scikit-learn for introductory machine learning applications, and Python regular expressions for text and pattern processing.
This course is intended for students, researchers, and professionals seeking practical programming skills for scientific computing, data analysis, and computational research. The course is also a required component of both the Micro-Credential in Data Science and the Micro-Credential in Artificial Intelligence programs. For additional information about these programs, please contact HPE DSI at contact@hpedsi.uh.edu.
Prerequisites: None
Date: 27th Jan 2026 - 3rd Mar 2026
Time: Tue Thur, 10:00 AM - 11:30 AM
Instructor: Dr. Jerry Ebalunode
Teaching Assistant: Okeowo, Temitayo (tkokeowo@cougarnet.uh.edu)
Class Capacity: 150
Location: Online (Microsoft Teams)
Clear Lake, Victoria, Downtown, Sugar Land, or Katy campuses
Attendees who are current UHS students, staff, or faculty from the Clear Lake, Victoria, Downtown, Sugar Land, or Katy campuses MUST fill in this credentials form at least three(3) weeks before the course start date. This will allow adequate time to process your course access credentials before the first class.
Current UHS (all campuses) Student, Staff, or Faculty Registration Fee: Free.
UH Alumni and Non-UH Affiliates
Attendees who are not current UHS students, staff, or faculty will need to make a payment for the course before its commencement.
UH Alumni Registration Fee: $250.00.
Non-UH Affiliate Registration Fee: $250.00.
** 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 using this link
(2) fill in this credentials form at least three(3) weeks before the course start date. This will allow adequate time to process your course access credentials before the first class.
If you don't wish to continue participating in the course, Please use the option "Unenroll me" available at the right-hand pane on the course webpage to unenroll from the course. Feel free to e-mail us at contact@hpedsi.uh.edu if you have questions.
** The following refund schedule applies:
More than three weeks before the start date: A cancellation fee of 10% of the total workshop cost applies.
Less than three weeks before the start date: A 15% cancellation fee applies.
Less than one week before the start date: A 25% cancellation fee applies.
48 hours or less before class starts: No refund is available.
All deposits and payments made are non-transferable. The HPE DSI cannot provide refunds, transfer payments, or offer makeup sessions for classes a student might miss, for any reason. If the HPE DSI has to cancel a workshop, you will receive a full refund.
This course is part of the Micro-credential in Data Science Program. Ask about this program at contact@hpedsi.uh.edu.
This tutorial will provide hands-on skills in using modern data visualization and analysis platforms, specifically the open-source parallel ParaView and Tableau. ParaView is 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, building 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.
Date: 27th May 2026 - 29th June 2026
Time: Mon Wed 1:00 PM - 2:30 PM
Instructor: Ishita Sharma, MS
Teaching Assistant: Praveen Kumar Gorrepati (pgorrepa@cougarnet.uh.edu)
Class Capacity: 150
Location: Microsoft Teams
-
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 course's starting date to allow for proper registration.
- I request everyone to join the classes when it is started by the Instructor or the TA.
- If the meeting has already started, please just join the meeting using the join option, don't start a new meeting or restart the meeting by yourself which would cause a lot of confusion as they would redirect you to a different meeting room.
Attendance Requirement:
Good standing on Attendance grade (>50%) would be required to see new course materials, homework assignments, and exams/projects as the course proceeds.
Students aiming to earn a badge or certificate for completing this course must meet the attendance requirement. To pass and receive the badge, you need to attend at least 12 of the 15 total hours of live sessions.
Clear Lake, Victoria, Downtown, Sugar Land, or Katy campuses
Attendees who are current UHS students, staff, or faculty from the Clear Lake, Victoria, Downtown, Sugar Land, or Katy campuses MUST fill in this credentials form at least three(3) weeks before the course start date. This will allow adequate time to process your course access credentials before the first class.
Current UHS (all campuses) Student, Staff, or Faculty Registration Fee: Free.
UH Alumni and Non-UH Affiliates
Attendees who are not current UHS students, staff, or faculty will need to make a payment for the course prior to its commencement.
UH Alumni Registration Fee: $250.00. See refund policy
Non-UH Affiliate Registration Fee: $250.00. See refund policy
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 using this payment link: https://store.mynsm.uh.edu/index.php?route=product/product&product_id=410&search=251+Data
(2) fill in this credentials form at least three(3) weeks before the course start date. This will allow adequate time to process your course access credentials before the first class.
If you don't wish to continue participating in the course, Please use the option "Unenroll me" available at the right-hand pane on the course webpage to unenroll from the course. Feel free to e-mail us at contact@hpedsi.uh.edu, if you have questions.
The following refund schedule applies:
More than three weeks before the start date: A cancellation fee of 10% of the total workshop cost applies.
Less than three weeks before the start date: A 15% cancellation fee applies.
Less than one week before the start date: A 25% cancellation fee applies.
48 hours or less before class starts: No refund is available.
All deposits and payments made are non-transferable. The HPE DSI cannot provide refunds, transfer payments, or offer makeup sessions for classes a student might miss, for any reason. If the HPE DSI has to cancel a workshop, you will receive a full refund.
This course is part of the Micro-credential in Data Science Program. Ask about this program at contact@hpedsi.uh.edu.
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.
Pre-requisites: Familiarity with Python Programming language
Recommended: Intro to Linux/Cluster computing course provided by HPE DSI
Instructor: Ishita Sharma
Dr. Jerry Ebalunode
Teaching Assistant: Praveen Kumar Gorrepati (pgorrepa@cougarnet.uh.edu)
Date: 26th May 2026 - 30th June 2026
Time: Mon Wed 2:30 PM - 4:00 PM
Location: Join Microsoft Teams with CODE
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.
Clear Lake, Victoria, Downtown, Sugar Land, or Katy campuses
Attendees who are current UHS students, staff, or faculty from the Clear Lake, Victoria, Downtown, Sugar Land, or Katy campuses MUST fill in this credentials form at least three(3) weeks before the course start date. This will allow adequate time for processing your course access credentials before the first class.
Current UHS (all campuses) Student, Staff, or Faculty Registration Fee: Free.
UH Alumni and Non-UH Affiliates
Attendees who are not current UHS students, staff, or faculty will need to make a payment for the course prior to its commencement.
UH Alumni Registration Fee: $250.00.
Non-UH Affiliate Registration Fee: $250.00.
** 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 using this link https://store.mynsm.uh.edu/index.php?route=product/product&product_id=402&search=261
(2) fill in this credentials form at least three(3) weeks before the course start date. This will allow adequate time to process your course access credentials before the first class.
If you don't wish to continue participating in the course, Please use the option "Unenroll me" available at the right-hand pane on the course webpage to unenroll from the course. If you have questions, e-mail us at contact@hpedsi.uh.edu
** The following refund schedule applies:
More than three weeks before the start date: A cancellation fee of 10% of the total workshop cost applies.
Less than three weeks before the start date: A 15% cancellation fee applies.
Less than one week before the start date: A 25% cancellation fee applies.
48 hours or less before class starts: No refund is available.
All deposits and payments made are non-transferable. The HPE DSI cannot provide refunds, transfer payments, or offer makeup sessions for classes a student might miss, for any reason. If the HPE DSI has to cancel a workshop, you will receive a full refund.
***This course is part of the Micro-credential in Data Science Program. Ask about this program at contact@hpedsi.uh.edu.
Machine learning is the science of developing statistical methods that quantify relationships within data. This branch of mathematics/computer science has seen 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 analytics. 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 the classification of images, signals, and features.
Prerequisites: Familiarity with Python Programming
Dates: 26th May 2026 - 30th June 2026
Time: Tue Thur 2:30 PM - 4:00 PM
Instructor: Dr. Ioannis Konstantinidis (ikonstan@Central.UH.EDU)
Teaching Assistant: Arun Reddy Karnati (akarnat2@cougarnet.uh.edu)
Location: Microsoft Teams with CODE : TBD
Class 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.
Attendance Requirement:
Students interested in getting a badge or certificate for completing this course, an attendance grade of at least 12 hours of the class meeting sessions is required, to be qualified for passing the course and getting the badge.
Clear Lake, Victoria, Downtown, Sugar Land, or Katy campuses
Attendees who are current UHS students, staff, or faculty from the Clear Lake, Victoria, Downtown, Sugar Land, or Katy campuses MUST fill in this credentials form at least three(3) weeks before the course start date. This will allow adequate time to process your course access credentials before the first class.
Current UHS (all campuses) Student, Staff, or Faculty Registration Fee: Free.
UH Alumni and Non-UH Affiliates
Attendees who are not current UHS students, staff, or faculty will need to make a payment for the course prior to its commencement.
UH Alumni Registration Fee: $250.00.
Non-UH Affiliate Registration Fee: $250.00.
** 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 using this link
https://store.mynsm.uh.edu/index.php?route=product/product&product_id=404&search=311
(2) fill in this credentials form at least three(3) weeks before the course start date. This will allow adequate time to process your course access credentials before the first class.
If you don't wish to continue participating in the course, Please use the option "Unenroll me" available at the right-hand pane on the course webpage to unenroll from the course. If you have questions, e-mail us at contact@hpedsi.uh.edu
** The following refund schedule applies:
More than three weeks before the start date: A cancellation fee of 10% of the total workshop cost applies.
Less than three weeks before the start date: 15% cancellation fee applies.
Less than one week before the start date: 25% cancellation fee applies.
48 hours or less before class start: No refund is available.
All deposits and payments made are non-transferable. The HPE DSI cannot provide refunds, transfer payments, or offer makeup sessions for classes a student might miss, for any reason. If the HPE DSI has to cancel a workshop, you will receive a full refund.
Deep learning refers to AI/ML techniques that utilize multilayer (deep) artificial neural networks. This branch of data science has seen exponential improvements in performance as our ability to collect, store, and process digital data has dramatically increased. Prediction, classification, regression, and identification of semi/unstructured data are areas where deep learning techniques exhibit a significant comparative advantage.
Course aims:
- To obtain an overview of the literature on deep learning methods and applications.
- To obtain an understanding of a variety of deep learning techniques for classification, regression, and prediction.
- To obtain the ability to implement and experiment with a wide range of deep learning algorithms in Python with examples: e.g., convolutional networks (CNN), auto-encoders, generative adversarial networks (GAN), transformers/attention (BERT)
- To understand and implement deep learning-based methods for the classification of semi/unstructured data such as images or language.
Prerequisites: HPE DSI 311 – Introduction to Machine Learning.
Dates: 7th July 2026 - 6th August 2026
Time: Tues Thurs 2:30 PM - 4:00 PM
Instructors: Dr. Ioannis Konstantinidis (ikonstantinidis@uh.edu)
Teaching Assistant: Sathwik Sangeetham (ssangeet@cougarnet.uh.edu)
Class Capacity: 150
Location: Online (Microsoft Teams)
-
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 course's starting date to allow for proper registration.
Clear Lake, Victoria, Downtown, Sugar Land, or Katy campuses
Attendees who are current UHS students, staff, or faculty from the Clear Lake, Victoria, Downtown, Sugar Land, or Katy campuses MUST fill in this credentials form at least three(3) weeks before the course start date. This will allow adequate time to process your course access credentials before the first class.
Current UHS (all campuses) Student, Staff, or Faculty Registration Fee: Free.
UH Alumni and Non-UH Affiliates
Attendees who are not current UHS students, staff, or faculty will need to make a payment for the course prior to its commencement.
UH Alumni Registration Fee: $250.00. See refund policy
Non-UH Affiliate Registration Fee: $250.00. See refund policy
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 using this payments link.
(2) fill in this credentials form at least three(3) weeks before the course start date. This will allow adequate time to process your course access credentials before the first class.
If you need to cancel a course for any reason, e-mail us at contact@hpedsi.uh.edu
The following refund schedule applies:
More than three weeks before the start date: A cancellation fee of 10% of the total workshop cost applies.
Less than three weeks before the start date: A 15% cancellation fee applies.
Less than one week before the start date: A 25% cancellation fee applies.
48 hours or less before class starts: No refund is available.
All deposits and payments made are non-transferable. The HPE DSI cannot provide refunds, transfer payments, or offer makeup sessions for classes a student might miss, for any reason. If the HPE DSI has to cancel a workshop, you will receive a full refund.