Zeit: Mittwoch, der 28.9., von 9-16 Uhr
Ort: via Zoom, bitte hier registrieren: https://wwu.zoom.us/meeting/register/u5ckcOCgrz4pGtGoouT28hn395X3ZL7_0Upd (Teilnehmerzahl nicht limitiert)
Sprache: Englisch
Programm:
09-10 Uhr Introduction: Data science infrastructure at WWU and NWZ (IVV NWZ)
incl. an overview of Incub.AI.tor by Friedrich Bach/Jonathan Wandscheer (REACH EUREGIO Start-up Center)
Slides Korth, Slides Bach/Wandscheer
10-11 Uhr Python libraries for data science (Jonathan Radas, WWU-IT)
Python is considered one of the most popular programming languages for data science. However, not only the language, but especially the community and tools help to make the language so valuable. This talk presents helpful libraries for data analysis and visualization: Starting with popular ones like pandas up to hidden gems for specific tasks.
11-12:30 Uhr Dimensionality reduction (Prof. Benjamin Risse, WWU)
Slides: https://www.dropbox.com/s/85w3n4v1pssm7a9/Risse-Dimensionality_Reduction.pdf?dl=0
12:30-14 Uhr Mittag
14-15 Uhr Model order reduction with pyMOR (Stephan Rave, WWU)
Slides: https://www.wwu.de/AMM/includes/ohlberger/team/rave/talks/cmtc_2022.pdf
15-16 Uhr InterKIWWU -- An interdisciplinary KI teaching initiative at WWU (Oliver Kamps, CeNoS)
The rapid development of the technological possibilities for generating, combinig and processing data continuously opens up new possibilities for the use of methods of artificial intelligence and machine learning in research, development and application. Solid knowledge in these areas is therefore important for students and researchers from different disciplines.
The interdisciplinary teaching program on machine learning and artificial intelligence (InterKIWWU) has the goal to develop university-wide courses to give all students the opportunity to acquire knowledge in these areas. The program includes introductory and advanced courses as well as teaching materials and courses on various social issues linked to artificial intelligence.