- https://www.nat-esm.de/services/trainings/events/data-analytics-for-engineering-data-using-machine-learning
- Data analytics for engineering data using machine learning
- 2025-03-10T08:30:00+01:00
- 2025-03-12T12:30:00+01:00
- A three-day workshop on data analytics for simulation data using machine learning
Mar 10, 2025
08:30 AM
to
Mar 12, 2025
12:30 PM
(Europe/Berlin / UTC100)
Online
As part of the EXCELLERAT P2 training program, Fraunhofer SCAI in cooperation with HLRS offers a three-day workshop on data analytics for simulation data using machine learning.
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 (see also the SimExplore tool).
Learning outcomes
- Basic knowledge on important machine learning methods to analyze numerical simulation data.
- Moreover, practical experience in applying these methods.
Target audience
Researchers, developers and industrial end users interested in new ways to analyze and visualize numerical simulation data.
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
Agenda
CET times:
Day 1: March 10, 2025
- 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: March 11, 2025
- 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: March 12, 2025
- 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 will be already available on the EXCELLERAT Portal (specific course page under construction).
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 Monday, February 24, 2025.
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.
If you are an EXCELLERAT Member, special conditions are available.