Suchergebnis: Lehrveranstaltungen im Frühjahrssemester 2019
Data Science Master | |||||||||||||||||||||
Kernfächer | |||||||||||||||||||||
Wählbare Kernfächer | |||||||||||||||||||||
Nummer | Titel | Typ | ECTS | Umfang | Dozierende | ||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
401-0674-00L | Numerical Methods for Partial Differential Equations Nicht für Studierende BSc/MSc Mathematik | W | 8 KP | 2G + 2P + 4A | |||||||||||||||||
401-0674-00 G | Numerical Methods for Partial Differential Equations This course is designed in a flipped classroom format. Attendance at the question and answer session ("Zentralübung") on Mondays 15-17 is expected. In addition, a Study Center is offered Mon 17-21 in HG E 41. | 2 Std. |
| R. Hiptmair | |||||||||||||||||
401-0674-00 P | Numerical Methods for Partial Differential Equations Homework C++ coding projects for the course "Numerical Methods for Partial Differential Equations" | 2 Std. | R. Hiptmair | ||||||||||||||||||
401-0674-00 A | Numerical Methods for Partial Differential Equations Video guided self-study or group-study for the course "Numerical Methods for Partial Differential Equations" | 4 Std. | R. Hiptmair | ||||||||||||||||||
401-3052-05L | Graph Theory | W | 5 KP | 2V + 1U | |||||||||||||||||
401-3052-05 V | Graph Theory | 28s Std. |
| B. Sudakov | |||||||||||||||||
401-3052-05 U | Graph Theory | 7s Std. |
| B. Sudakov | |||||||||||||||||
401-3052-10L | Graph Theory | W | 10 KP | 4V + 1U | |||||||||||||||||
401-3052-10 V | Graph Theory | 4 Std. |
| B. Sudakov | |||||||||||||||||
401-3052-10 U | Graph Theory | 1 Std. |
| B. Sudakov | |||||||||||||||||
401-3602-00L | Applied Stochastic Processes | W | 8 KP | 3V + 1U | |||||||||||||||||
401-3602-00 V | Applied Stochastic Processes | 3 Std. |
| V. Tassion | |||||||||||||||||
401-3602-00 U | Applied Stochastic Processes Thu 9-10 or Thu 12-13 | 1 Std. |
| V. Tassion | |||||||||||||||||
401-4627-00L | Empirical Process Theory with Applications in Statistics and Machine Learning | W | 4 KP | 2V | |||||||||||||||||
401-4627-00 V | Empirical Process Theory with Applications in Statistics and Machine Learning | 2 Std. |
| S. van de Geer | |||||||||||||||||
401-4632-15L | Causality | W | 4 KP | 2G | |||||||||||||||||
401-4632-15 G | Causality | 2 Std. |
| C. Heinze-Deml | |||||||||||||||||
401-4904-00L | Combinatorial Optimization | W | 6 KP | 2V + 1U | |||||||||||||||||
401-4904-00 V | Combinatorial Optimization takes place in HG G 19.1 with the following exceptions: 21 February, 14 March and 21 March 2019 in HG D 1.2 | 2 Std. |
| R. Zenklusen | |||||||||||||||||
401-4904-00 U | Combinatorial Optimization Starts in the second week of the semester. | 1 Std. |
| R. Zenklusen | |||||||||||||||||
401-6102-00L | Multivariate Statistics | W | 4 KP | 2G | |||||||||||||||||
401-6102-00 G | Multivariate Statistics | 2 Std. |
| N. Meinshausen | |||||||||||||||||
701-0104-00L | Statistical Modelling of Spatial Data | W | 3 KP | 2G | |||||||||||||||||
701-0104-00 G | Statistical Modelling of Spatial Data | 2 Std. |
| A. J. Papritz | |||||||||||||||||
227-0224-00L | Stochastic Systems | W | 4 KP | 2V + 1U | |||||||||||||||||
227-0224-00 V | Stochastic Systems Findet dieses Semester nicht statt. | 2 Std. | |||||||||||||||||||
227-0224-00 U | Stochastic Systems Findet dieses Semester nicht statt. | 1 Std. | |||||||||||||||||||
401-3622-00L | Regression | W | 8 KP | 4G | |||||||||||||||||
401-3622-00 G | Regression Findet dieses Semester nicht statt. planned to be offered in the Autumn Semester 2019 as a yearly recurring course with new course title: Statistical Modelling | 4 Std. | keine Angaben | ||||||||||||||||||
Interdisziplinäre Wahlfächer | |||||||||||||||||||||
Nummer | Titel | Typ | ECTS | Umfang | Dozierende | ||||||||||||||||
101-0478-00L | Measurement and Modelling of Travel Behaviour | W | 6 KP | 4G | |||||||||||||||||
101-0478-00 G | Measurement and Modeling of Travel Behaviour | 4 Std. |
| K. W. Axhausen | |||||||||||||||||
103-0228-00L | Multimedia Cartography Voraussetzung: Erfolgreicher Abschluss der Lerneinheit Cartography III (103-0227-00L). | W | 4 KP | 3G | |||||||||||||||||
103-0228-00 G | Multimedia Cartography | 3 Std. |
| H.‑R. Bär, R. Sieber | |||||||||||||||||
103-0247-00L | Mobile GIS and Location-Based Services | W | 5 KP | 4G | |||||||||||||||||
103-0247-00 G | Mobile GIS and Location-Based Services | 4 Std. |
| P. Kiefer | |||||||||||||||||
103-0255-01L | Geodatenanalyse | W | 2 KP | 2G | |||||||||||||||||
103-0255-01 G | Geodatenanalyse | 2 Std. |
| R. Buffat | |||||||||||||||||
227-0945-10L | Cell and Molecular Biology for Engineers II This course is part II of a two-semester course. Knowledge of part I is required. | W | 3 KP | 2G | |||||||||||||||||
227-0945-10 G | Cell and Molecular Biology for Engineers II | 2 Std. |
| C. Frei | |||||||||||||||||
227-0391-00L | Medical Image Analysis Basic knowledge of computer vision would be helpful. | W | 3 KP | 2G | |||||||||||||||||
227-0391-00 G | Medical Image Analysis | 2 Std. |
| E. Konukoglu, M. A. Reyes Aguirre, C. Tanner | |||||||||||||||||
261-5113-00L | Computational Challenges in Medical Genomics Number of participants limited to 20. | W | 2 KP | 2S | |||||||||||||||||
261-5113-00 S | Computational Challenges in Medical Genomics | 2 Std. |
| A. Kahles, G. Rätsch | |||||||||||||||||
261-5120-00L | Machine Learning for Health Care Number of participants limited to 78. Previously called Computational Biomedicine II | W | 4 KP | 3P | |||||||||||||||||
261-5120-00 P | Machine Learning for Health Care | 3 Std. |
| G. Rätsch | |||||||||||||||||
262-0200-00L | Bayesian Phylodynamics | W | 4 KP | 2G + 2A | |||||||||||||||||
262-0200-00 G | Bayesian Phylodynamics | 2 Std. |
| T. Stadler, T. Vaughan | |||||||||||||||||
262-0200-00 A | Bayesian Phylodynamics | 2 Std. | T. Stadler, T. Vaughan |
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