Data Analytics for Engineering Data using Machine Learning

Description

This three-day online workshop addresses the preparation, analysis and interpretation of numerical simulation data by machine learning methods. Besides the introduction of the most important concepts like clustering, dimensionality reduction, visualization and prediction, this course provides several practical hands-on tutorials using the python libraries numpy, scikit-learn and pytorch as well as the SCAI DataViewer.

 

Location

Online course
Organizer: HLRS, University of Stuttgart, Germany

Prerequisites and content levels

Prerequisites

• Preliminary experience with Python is required. Since Python is used, the following tutorial can be used to learn the syntax.
• Preliminary experience in using Jupyter Notebook is also required.

Content levels

• Beginners' level: 4 hours
• Intermediate level: 5 hours
• Community level: 5 hours

Learn more about course curricula and content levels.

Instructors

Arno Feiden, Christian Gscheidle and Daniela Steffes-lai (Fraunhofer SCAI)

Agenda

CEST times:

Day 1: Monday, April 20, 2026

• 08:45-09:00 Drop in to the videoconference
• 09:00-12:30 Introduction to machine learning methods like clustering and dimensionality reduction by means of short practical exercises in python
• 12:30-13:30 Lunch break
• 13:30-17:00 Application of the methods from the previous session to numerical simulation data stemming from engineering applications with the help of the SCAI DataViewer

Day 2: Tuesday, April 21, 2026

• 08:45-09:00 Drop in to the videoconference
• 09:00-12:30 Introduction to prediction by deep learning methods together with hands-on exercises using the software library pyTorch

Day 3: Wednesday, April 22, 2026

• 08:45-09:00 Drop in to the videoconference
• 09:00-12:30 Introduction to interpretability of machine learning methods with the help of the examples from the previous session

Registration information

Apply here.

Registration will close as soon as the course capacity is reached.

Fees

The course is open and free of charge for participants from academia, industry, and public administration from the Member States (MS) of the European Union (EU) and Associated/Other Countries to the Horizon Europe programme.

Contact

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

Christian Gscheidle (Fraunhofer SCAI), christian.gscheidle(at)scai.fraunhofer.de

Arno Feiden (Fraunhofer SCAI), arno.feiden(at)scai.fraunhofer.de

 

HLRS Training Collaborations in HPC and AI

HLRS is part of the Gauss Centre for Supercomputing (GCS), together with JSC in Jülich and LRZ in Garching near Munich.  is the German National Competence Centre (NCC) for High-Performance Computing. HLRS is also a member of the Baden-Württemberg initiative bwHPC. Since 2025, HLRS coordinates HammerHAI. 

 

More information & registration here.