Tutorials and Courses
Overview
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.
Cost:
- 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 in the Spring semester). 201 C++ (offered only in the Spring semester) provides a scientific programming background for most users. Students interested in parallel programming, such as 303 GPU Programming (offered only in the Spring semester), should have knowledge of low-level programming languages such as C++ or Fortran. Upon completing 212 Python, 211 R, 271 Excel (offered only in the Fall and Spring semesters), 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 the 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. 313 Introduction to Natural Language Processing and Large Language Models (offered every semester) requires 311 Machine Learning. 400 Introduction to Bioinformatics and NGS Data Analysis (offered in Fall and Spring semesters) requires 212 Python and 261 Principles of Data Management. 411 Selected Topics in AI (offered in Fall and Spring semesters) requires 311 Machine Learning and 312 Deep Learning.
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.
COURSE DESCRIPTIONS
DSI 400: Introduction to Bioinformatics and NGS Data Analysis
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; 27th August 2024 - 01st October 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.
- 101 Introduction to Cluster Computing
Mon Wed 01/22/2025 - 02/26/2025, 10:30 AM - 12:00 PM
- 201 Scientific Computing in C++
Mon Wed 03/17/2025 - 04/21/2025, 10:30 AM - 12:00 PM
- 211 Data Analysis in R
Mon Wed 01/22/2025 - 02/26/2025, 02:30 PM - 04:00 PM
- 212 Scientific Programming with Python
Tue Thur 1/21/2025 - 02/25/2025, 10:30 AM - 12:00 PM
- 251 Data Visualization using ParaView and Tableau
Mon Wed 3/17/2025 - 4/21/2025, 1:00 PM - 2:30 PM
- 261 Principles of Data Management
Tue Thur 01/21/2025 - 02/25/2025, 1:00 PM - 2:30 PM
- 271 Data Analysis & Visualization in Excel & Power BI
Tue Thur 01/21/2025 - 02/25/2025, 2:30 PM - 4:00 PM
- 302 Parallel Computing with MPI
Tue Thur 3/18/2025 - 4/22/2025, 2:30 PM - 4:00 PM
- 303 GPU Programming
Tue Thur 03/18/2025 - 04/22/2025, 10:30AM - 12:00 PM
- 311 Introduction to Machine Learning
Tue Thur 01/21/2025 - 02/25/2025, 2:30 PM - 4:00 PM
- 312 Introduction to Deep Learning
Tue Thur 3/18/2025 - 4/22/2025, 2:30 PM - 4:00 PM
- 400 Introduction to Bioinformatics and NGS Data Analysis
Tue Thu 01/21/2025 - 02/25/2025, 2:30 PM - 4:00 PM
Registration
UH Students
- Login to Moodle to sign up for each course (access this link via campus WIFI or the UH VPN).
Non-UH/Alumni
- 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 contact@hpedsi.uh.edu for additional information.
Badgr Instructions
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.