Vorlesungen Data Science
Herbstsemester 2023
Titel | Dozierende | KP | Zeit | |
Mathematical Foundations | ||||
66096 | Mathematics of Data Science * | Jiří Černý | 8 KP | Mo 16:15-18:00 |
12246 | Marcus J. Grote | 8 KP | Mo 14:15-16:00 | |
19300 | Random Processes: Theory and applications from physics to finance | Jörg Lehman | 4 KP | Mi 09:00-10:15 |
22738 | Iterative Verfahren der Numerik (nur jedes 2. Herbstsemester) | Helmut Harbrecht | 4 KP | Mo 14:15-16:00 |
Machine Learning Foundations | ||||
45401 | Volker Roth | 4 KP | Do 14:15-16:00 | |
66937 | Aurelien Lucchi | 6 KP | Mo 10:15-12:00 | |
Systems Foundations | ||||
45402 | Florina M. Ciorba | 8 KP | Do 10:15-12:00 | |
15731 | Roger Weber | 6 KP | Fr 15:15-18:00 | |
Electives in Data Science | ||||
11680 | Computational Physics | Stefan Goedecker | 4 KP | Mo 10:15-12:00 |
11681 | Computational Physics | Stefan Goedecker | 2 KP | |
12246 | Marcus J. Grote | 8 KP | Mo 14:15-16:00 | |
15731 | Roger Weber | 6 KP | Fr 15:15-18:00 | |
17163 | Craig Hamilton | 6 KP | Mi 10:15-12:00 | |
18545 | Advanced Mathematics for Economics | Thomas Zehrt | 3 KP | Block: 04.09.2023 - 15.09.2023 |
19300 | Random processes: Theory and applications from physics to finance | Jörg Lehmann | 4 KP | Mi 09:00-10:15 |
25637 | Molecular Simulations with Chemical and Biological Applications | Markus Meuwly | 3 KP | Do 16:15-18:00 |
41828 | Perspectives of Natural Sciences on Sustainability | Patrizia Holm | 3 KP | Di 14:15-16:00 |
41829 | Perspectives of Social Sciences on Sustainability | Basil Bornemann | 3 KP | Di 16:15-18:00 |
45400 | Malte Helmert | 8 KP | Mo 14:15-16:00 | |
45401 | Volker Roth | 4 KP | Do 14:15-16:00 | |
55048 | The AI Economy: Business Strategies and Policy Issues | Stephan Weymouth | 3 KP | Block: 07.08.2023 - 17.08.2023 |
55662 | Applied Mathematics and Informatics in Drug Discovery | David Zhang Jitao | 2 KP | Fr 12:15-14:00 |
55769 | Statistical Modelling | Giusi Moffa | 6 KP | Di 14:15-16:00 |
66937 | Aurelien Lucchi | 6 KP | Mo 10:15-12:00 |
* Diese Vorlesungen sind für alle Data Science Studenten Pflicht. Die übrigen Vorlesungen in den einzelnen Modulen können anhand der vorgegebenen Empfehlungsliste frei gewählt werden.