Nov 04, 2024 09:00 AM to Dec 13, 2024 10:00 AM
(Europe/Berlin / UTC100)



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0711 685 87233

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For a long time, artificial intelligence (AI) was just an empty buzzword. Nowadays, AI has already left the development labs and entered everyday life. Artificial intelligence algorithms and systems are omnipresent. Be it the recommendation of products on Amazon, series recommendations in Netflix or interaction with voice assistants such as Alexa or Cortana. This module is intended to provide an initial insight into the "black box of data analysis". This includes not only the definition of relevant core terms, but also their differentiation. In this module, you will gain an initial insight into the typical data analysis process ("workflow") using specific examples. The examples are supplemented by a series of practical examples. This course also offers the opportunity for an intensive exchange with the lecturers and other course participants.

Subject areas
  • Data analysis, artificial intelligence: an introduction
  • Convergence of HPC and artificial intelligence
  • Excursus: Container technologies
  • Exploratory data analysis
  • Excursus: Non-relational databases
  • Machine learning: concepts, algorithms and evaluation
  • Introduction to neural networks
  • Big data architectures and frameworks
  • Trends and new technologies in the field of HPC and AI
Exercises on the training cluster of the Supercomputing Academy
  • Exercise on container technologies
  • Exercise on exploratory data analysis with Tableau and Python
  • Exercise on neural networks with TensorFlow
  • Exercise on data analysis using the example of Stuttgart S-Bahn travel times

The exercises will be carried out on the training cluster of the HLRS of the Supercomputing Academy. Participants receive 24/7 access to the cluster for the entire duration of the course. 50% of the exercises are carried out with a Jupyter notebook on the training cluster. The exercise on exploratory data analysis and the exercise on neural networks are also processed via a container, so that participants can export their containers, take the exercises with them and run them on another host system (which has container visualization software installed) without any problems. Apache Spark (a framework for cluster computing) is used for the data analysis exercise using the example of Stuttgart's S-Bahn journey times.

  • 52,50€ Student without a Master's degree (or equivalent)
  • 127.50€ Employee or doctoral candidate at a German university or a German public research institute
  • 255.00€ Staff member or doctoral candidate at a university or public research institute in an EU, EU-associated or PRACE country other than Germany
  • 510.00€ Employee or doctoral candidate at a university or public research institute outside an EU, EU-associated or PRACE country
  • 1410.00€ Other participants, e.g. from industry, other public institutions or private participation

Target groups
  • Development engineers
  • CAE, calculation and simulation engineers
  • System designers
  • Those interested in simulation

Please check the event website for specific prior knowledge.

Time required

The time required per module is 50 hours in total, with free time allocation on a weekly basis and fixed dates for virtual seminars (evenings) and examinations (during the day). The duration extends over 5 weeks with an approximate weekly workload of 10 hours.

Flexible learning

You learn conveniently and effectively online. The online phases are supplemented by regular online meetings in the virtual classroom. Participants can apply what they have learned in exercises on the training cluster at their own pace. The HLRS experts who developed the learning units are available to answer questions in weekly virtual seminars. A forum enables participants to exchange technical information with each other.

Qualified confirmation of participation

You will receive a certificate of attendance from the High Performance Computing Center Stuttgart for participating in the module. If you have also completed all of the module's learning content, regularly participated in the virtual seminars and answered the learning tasks correctly, you will receive a qualified confirmation of participation.


You will receive a certificate if you meet the requirements for the qualified confirmation of attendance and pass the module's final examination. By successfully passing the exam, you prove that you have acquired the skills to apply the knowledge you have learned independently.

Further information

For more information about the Supercomputing Academy, please visit our website: https://www.supercomputing-akademie.de/