Höchstleistungsrechenzentrum Stuttgart: Supercomputing Academy: Data Analysis with HPC

Prerequisites and content levels

Prerequisites

Basic knowledge of the Linux/Unix operating system, including shell commands, secure shell (SSH), file and script management, system structure, user permissions, and basic batch script editing (e.g., nano, vim, or emacs).
Basic knowledge of Python or solid experience in another programming language (e.g., C/C++, Fortran, or Java) and the ability to quickly learn Python. Familiarity with Python libraries such as matplotlib, pandas, numpy, and seaborn, as well as experience using Jupyter Notebooks.

Content levels

Beginners: 24 hours
Intermediate: 16 hours
Advanced: 12 hours

Learn more about course curricula and content levels.

Target audience

This course is intended for, but is not limited to, the following groups:

HPC users interested in applying AI and data analytics workflows.
Engineers and researchers seeking practical skills in data analysis, machine learning, and container technologies.
Professionals and enthusiasts aiming to stay updated on the latest trends and emerging technologies in AI and Big Data.

Learning outcomes

After completing this course, participants will:

Understand and apply core concepts and methodologies of data analysis and machine learning.
Effectively utilize advanced tools like TensorFlow and Apache Spark.
Conduct exploratory data analysis, implement machine learning algorithms, and build neural network models.
Leverage container technologies to efficiently manage analytical workflows across diverse computing environments.
Stay informed about current trends and new developments in HPC and AI technologies.

Instructors

Dr. -Ing. Lorenzo Zanon (HLRS) lorenzo.zanon(at)hlrs.de and
Junghwa Lee (HLRS) junghwa.lee(at)hlrs.de

Agenda

Week 1: Introduction to Data Analysis and AI within HPC
Week 2: Machine Learning Algorithms and Model Evaluation
Week 3: Big Data Frameworks and Emerging HPC/AI Trends
Week 4-5: Practical Exercises in Data Pre-processing, Feature Engineering, and Machine Learning Applications

Dates for the Seminars and Exam (Preliminary schedule)

Seminars are scheduled on Thursdays, 17:30-19:00: Sep. 4 (kick-off), and Sep. 11, 18, 25, Oct 2, and Oct. 9 (discuss the content of weeks 1-5).
Exam is scheduled for Friday, Oct. 17. You may start the approximately 2-hour exam anytime between 06:00 and 23:00. The official course dates reflect the course weeks only, not your exam preparation or the exam itself.
Although the schedule is preliminary, we strongly recommend that you reserve these dates when you register for this course.

Registration information

Register via the button at the top of this page.
We encourage you to register to the waiting list if the course is full. Places might become available.

Registration closes on August 24, 2025.

Fees

0 Euro: Employees of the HLRS, or the Jülich Supercomputing Centre (JSC), or the Leibniz Supercomputing Centre (LRZ)
52,50 Euro: Students without master’s degree or equivalent
127,50 Euro: PhD students or employees at a German university or public research institute
255,00 Euro: PhD students or employees at a university or public research institute in an EU, EU-associated or PRACE country other than Germany
510,00 Euro: PhD students or employees at a university or public research institute outside of EU, EU-associated or PRACE countries
1410,00 Euro: Other participants, e.g., from industry, other public service providers, or government

Link to the EU and EU-associated (Horizon Europe), and PRACE countries.

HLRS concept for flexible learning

Flexible Learning

This course offers flexible learning, allowing you to learn at your own pace and access online course materials and cluster resources. Web-seminars are held weekly to discuss the learning modules and to answer your questions. We also provide forum channels that enable you to communicate with the lecturer and peers, as well as to share your experiences.

Learning Duration

The course is divided into multiple learning units of 10 hours each. Participants can learn the individual learning content on their own schedule. In addition, this course has fixed dates for virtual seminars and the exam.

Certificate & Attendance Confirmation

High-Performance Computing Center (HLRS) issues participants an attendance confirmation if they have attended all seminars, as well as a certificate if they have passed the exam at the end of the course.

Technical Requirement

Stable Internet connection so you can access and download the learning materials.
Access to video conferencing tool with camera and microphone for participation in regular seminars.

Contact

Junghwa Lee, phone 0711 685 87228, training(at)hlrs.de

HLRS Training Collaborations in HPC

HLRS is part of the Gauss Centre for Supercomputing (GCS), together with JSC in Jülich and LRZ in Garching near Munich. EuroCC@GCS is the German National Competence Centre (NCC) for High-Performance Computing. HLRS is also a member of the Baden-Württemberg initiative bwHPC.

This course is provided within the framework of the bwHPC training program.

Further courses

See the training overview and the Supercomputing Academy pages.