HLRS High Performance Computing Center Stuttgart: Data analytics for engineering data using machine learning

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

Bastian Bohn, Christian Gscheidle and Sara Hahner (Fraunhofer SCAI)

Agenda

CEST time:

Day 1: 12 June 2023

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: 13 June 2023

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: 14 June 2023

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

Handout

Notebooks and data of the equivalent 2022/ML4SIM4 course are already available on the EXCELLERAT Portal.

Updated exercises and slides will be made available during the course.

Registration information

Register at Fraunhofer SCAI via the button at the top of this page.

Registration closes on May 26, 2023.

Fees

Students without master’s degree or equivalent: 300 EUR
PhD students or employees at a German university or public research institute: 300 EUR
PhD students or employees at a university or public research institute in an EU, EU-associated or PRACE country other than Germany: 300 EUR
PhD students or employees at a university or public research institute outside of EU, EU-associated or PRACE countries: 600 EUR
Other participants, e.g., from industry, other public service providers, or government: 600 EUR

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

Contact

Lorenzo Zanon, phone 0711 685 63824, zanon(at)hlrs.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. EuroCC@GCS 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.

EXCELLERAT P2

This course is partly realised in cooperation with the Centre of Excellence EXCELLERAT P2 (funded by the European Union, grant agreement No 101092621). See also the EXCELLERAT Service Portal for more information.

Official course URL(s)

http://www.hlrs.de/training/2023/ML4SIM1, on the EXCELLERAT Portal, and course website at Fraunhofer SCAI.

Further courses

See the training overview and the Supercomputing Academy pages.

Data analytics for engineering data using machine learning

Location