HPE DSI awards digital Badges to students who complete and pass each of our courses. These courses do not affect students' University GPA or Grade Point.
We recommend you follow the HPE DSI course roadmap when picking courses.
- Free for active University of Houston System (UHS) students, staff or faculty
- $250/course badge for non-UH individuals
How does it work?
101 Intro to HPC (offered every semester) is designed for students beginning their training and is a prerequisite for all other HPE DSI courses. After completing this, a student can choose one or more script programming courses like 211 R (offered every semester), 212 Python (offered every semester) and or 221 Julia (offered only Spring semester). 201 C++ (offered only Spring semester), provides a scientific programming background for most users. Students interested in parallel programming for instance 303 GPU programming ( offered only Spring semester) should have knowledge of low-level programming language such as C++ or Fortran. Upon completing 212 Python, 211 R, 271 Excel (offered only Fall and Spring semester) and/or 221 Julia, students can take the 261 Principles of Data Management course (offered every semester) , followed by 311 Machine Learning (offered every semester) and then 312 Deep Learning(offered in Spring semester). 212 Python is a prerequisite for 261, 311 and 312. 311 Machine Learning is a prerequisite for 312 Deep Learning. 301 Parallel Programming with OpenMP and 302 Parallel Programming with MPI are offered only in the Fall semester.
Attendance is mandatory. Grades (Pass/Fail), and badges, will not be assigned to students who fail to attend at least 12 hours of synchronous instruction.
This special topic course will introduce students to the field of bioinformatics and the analysis of next-generation sequencing (NGS) data.
This course includes the following topics:
- Data QC
- Sequencing reads mapping
- Variant calling, and annotation
Prerequisites: Participants are expected to have basic knowledge of biology. Previous experience in programming and knowledge of the UNIX/Linux environment will be beneficial but is not necessary.
- Duration: Tuesday, Thursday; 23rd January 2024 - 27th February 2024
- Time: 2:30 pm – 4:00 pm, CST
- Location: Virtual via Microsoft TEAMS
UH HPC Clusters Introduction
This 90 minute weekly, live course covers introduction to connecting to UH clusters and running jobs in the cluster, and provides an opportunity to ask questions and learn about the latest HPE DSI HPC systems updates.
This workshop is designed from the perspective of helping students to begin their technical interview preparation journey.
This workshop will be covering the following topics:
- Data Structures & Algorithms
- OOPs concept
Please note: The course will follow the Python programming language. Topics are tentative.
- Programming Language: Python, SQL
- Duration: Course is generally offered in the summer.
- Location: in-person and virtual
- 101 Introduction to cluster computing: Linux, shell scripting, queuing systems, cluster architecture
Mon Wed 01/22/2024 - 02/26/2024, 10:30 AM to 12:00 PM
- 201 Scientific Computing in C++
Mon Wed 03/18/2024 - 04/22/2024, 10:30 AM to 12:00 PM
- 211 Data Analysis in R
Mon Wed 01/22/2024 - 02/21/2024, 2:30 PM to 4:00 PM
- 212 Scientific Programming with Python
Tue Thur 01/23/2024 - 02/27/2024, 10:30 AM to 12:00 PM
- 251 Data Visualization using ParaView and Tableau
Mon Wed 03/18/2024 - 04/17/2024, 1:00 PM - 2:30 PM
- 261 Principles of Data Management
Tues Thur 01/23/2024 - 02/22/2024, 1:00 PM to 2:30 PM
- 271 Data Analysis & Visualization in Excel & Power BI
Tue Thur 01/23/2024 - 02/27/2024, 2:30 PM to 04:00 PM
- 302 Parallel computing with MPI
Tue Thur 3/19/2024 - 4/23/2024, 2:30 PM - 4:00 PM
- 303 GPU Programming
Tue Thur 03/19/2024 - 04/23/2024, 10:30 AM to 12:00 PM
- 311 Introduction to Machine Learning
Tue Thur 01/23/2024 - 02/27/2024, 2:30 PM to 4:00 PM
- 312 Introduction to Deep Learning
Tue Thur 3/19/2024 - 4/18/2024, 2:30 PM to 4:00 PM
- 400 Introduction to Bioinformatics and NGS Data Analysis
Tue Thu 01/23/2024 - 02/27/2024, 2:30 PM to 4:00 PM
- Login to Moodle to sign up for each course (access this link via campus WIFI or the UH VPN).
- Complete the Non-UH Main Campus Affiliates HPE DSI course registration form at least three (3) weeks before course commencement. This will allow adequate time for processing of your course access credentials before the first-class meeting.
- Complete the payment of the course fees ($250.00 per course) at least three (3) weeks before course commencement. The URL and payment links are available on the course page. This will allow adequate time for processing of your course access credentials before the first-class meeting.
**You may email us at firstname.lastname@example.org for additional information.
Link your HPE DSI Badges to a Badgr account and share them on online platforms (e.g., LinkedIn). Create a Badgr account at badgr.io if you don’t already have one.
- Enter the sign in credentials for your Badgr account in the Moodle Backpack page to request to connect.
- If successful, the backpack status will change to “Verification pending”.
- Check the email account you registered with Badgr for a verification email from HPE DSI.
- Click on the verification link in the email to confirm and activate the connection of your Moodle backpack to your Badgr backpack.
- If successful, the link will take you to your Moodle Backpack page and the status will change to "connected".
- Go to the “manage my badges” page, where you will see a list of all your earned HPE DSI Badges.
- Click on the specific HPE DSI Badge you want to share; the link will take you to a details page about the Badge.
- Click on the "Add to Backpack" button.
- If successful, you will be taken back to the “manage my badges” page, which will now display an “Added badge to backpack” notice. You will also receive an email from Badgr noting that you have earned this Badge.
- Sign in to your badgr.io account.
- Select the Badge you want to share from the list.
- Click on “Share” to generate a URL or link it to social platforms; Click on "Download" to save it on your computer device.