Search result: Courses in Spring Semester 2020

Data Science Master Information
Core Courses
Core Electives
NumberTitleTypeECTSHoursLecturers
263-4400-00LAdvanced Graph Algorithms and Optimization Information Restricted registration - show details
Number of participants limited to 30.
W5 credits3G + 1A
263-4400-00 GAdvanced Graph Algorithms and Optimization3 hrs
Wed09:15-12:00CAB G 52 »
R. Kyng
263-4400-00 AAdvanced Graph Algorithms and Optimization1 hrsR. Kyng
263-5300-00LGuarantees for Machine Learning Information Restricted registration - show details W5 credits2V + 2A
263-5300-00 VGuarantees for Machine Learning
Special selection process. Preference is given to Masters and Doctorate students. If need be other criteria are degree program and previous courses taken.
2 hrs
Wed08:15-10:00CAB G 51 »
F. Yang
263-5300-00 AGuarantees for Machine Learning2 hrsF. Yang
401-0674-00LNumerical Methods for Partial Differential Equations
Not meant for BSc/MSc students of mathematics.
W10 credits2G + 2U + 2P + 4A
401-0674-00 GNumerical Methods for Partial Differential Equations
This course is designed in a flipped classroom format based on video tutorials and supplemented by a weekly question-and-answer session, for which attendance is highly recommended.
2 hrs
Mon15:00-17:00ER SA TZ »
15:15-17:00HG F 1 »
R. Hiptmair
401-0674-00 UNumerical Methods for Partial Differential Equations
Groups are selected in myStudies.
2 hrs
Fri10:00-12:00ER SA TZ »
10:00-12:00ER SA TZ »
10:15-12:00ETZ E 8 »
10:15-12:00HG D 1.1 »
10:15-12:00HG G 3 »
11:15-13:00ETZ G 91 »
R. Hiptmair
401-0674-00 PNumerical Methods for Partial Differential Equations
Homework C++ coding projects for the course "Numerical Methods for Partial Differential Equations"
2 hrsR. Hiptmair
401-0674-00 ANumerical Methods for Partial Differential Equations
Video guided self-study or group-study for the course "Numerical Methods for Partial Differential Equations"
4 hrsR. Hiptmair
401-3052-05LGraph Theory Information W5 credits2V + 1U
401-3052-05 VGraph Theory28s hrs
Wed/110:00-12:00ER SA TZ »
10:15-12:00HG E 5 »
Thu/110:00-12:00ER SA TZ »
10:15-12:00HG F 3 »
B. Sudakov
401-3052-05 UGraph Theory7s hrs
Thu/115:15-16:00CAB G 52 »
15:15-16:00CAB G 56 »
15:15-16:00HG E 21 »
17:15-18:00HG E 33.5 »
B. Sudakov
401-3052-10LGraph Theory Information W10 credits4V + 1U
401-3052-10 VGraph Theory4 hrs
Wed10:00-12:00ER SA TZ »
10:15-12:00HG E 5 »
Thu10:00-12:00ER SA TZ »
10:15-12:00HG F 3 »
B. Sudakov
401-3052-10 UGraph Theory1 hrs
Thu15:15-16:00CAB G 52 »
15:15-16:00CAB G 56 »
15:15-16:00HG E 21 »
17:15-18:00HG E 33.5 »
B. Sudakov
401-3602-00LApplied Stochastic Processes Information W8 credits3V + 1U
401-3602-00 VApplied Stochastic Processes
Does not take place this semester.
3 hrsnot available
401-3602-00 UApplied Stochastic Processes
Does not take place this semester.
1 hrsnot available
401-4632-15LCausality Information W4 credits2G
401-4632-15 GCausality2 hrs
Wed10:00-12:00ER SA TZ »
10:15-12:00HG E 1.1 »
C. Heinze-Deml
401-4944-20LMathematics of Data ScienceW8 credits4G
401-4944-20 GMathematics of Data Science
Planned to take place again in the Autumn Semester 2021.
4 hrs
Tue15:15-17:00HG F 7 »
Thu15:15-17:00HG G 3 »
A. Bandeira
401-6102-00LMultivariate StatisticsW4 credits2G
401-6102-00 GMultivariate Statistics
Does not take place this semester.
2 hrsnot available
402-0448-01LQuantum Information Processing I: Concepts
This theory part QIP I together with the experimental part 402-0448-02L QIP II (both offered in the Spring Semester) combine to the core course in experimental physics "Quantum Information Processing" (totally 10 ECTS credits). This applies to the Master's degree programme in Physics.
W5 credits2V + 1U
402-0448-01 VQuantum Information Processing I: Concepts2 hrs
Mon13:45-15:30HPV G 5 »
14:00-16:00ER SA TZ »
P. Kammerlander
402-0448-01 UQuantum Information Processing I: Concepts1 hrs
Mon15:45-16:30HCI H 8.1 »
15:45-16:30HCI J 4 »
15:45-16:30HIL E 10.1 »
15:45-16:30HPV G 5 »
16:00-17:00ER SA TZ »
P. Kammerlander
701-0104-00LStatistical Modelling of Spatial DataW3 credits2G
701-0104-00 GStatistical Modelling of Spatial Data2 hrs
Wed08:15-10:00CHN F 46 »
A. J. Papritz
Interdisciplinary Electives
NumberTitleTypeECTSHoursLecturers
101-0478-00LMeasurement and Modelling of Travel BehaviourW6 credits4G
101-0478-00 GMeasurement and Modeling of Travel Behaviour4 hrs
Wed09:45-11:30HIL F 36.1 »
Thu08:00-09:35HIL F 36.1 »
K. W. Axhausen
103-0228-00LMultimedia Cartography
Prerequisite: Successful completion of Cartography III (103-0227-00L).
W4 credits3G
103-0228-00 GMultimedia Cartography3 hrs
Tue08:00-10:30HIL G 22 »
H.‑R. Bär, R. Sieber
103-0247-00LMobile GIS and Location-Based ServicesW5 credits4G
103-0247-00 GMobile GIS and Location-Based Services4 hrs
Thu12:45-16:30HIL G 22 »
P. Kiefer
103-0255-01LGeodata AnalysisW2 credits2G
103-0255-01 GGeodatenanalyse2 hrs
Thu14:45-16:30HIL D 53 »
K. Kurzhals
227-0945-10LCell and Molecular Biology for Engineers II
This course is part II of a two-semester course.
Knowledge of part I is required.
W3 credits2G
227-0945-10 GCell and Molecular Biology for Engineers II2 hrs
Thu13:15-15:00ETZ F 91 »
C. Frei
227-0391-00LMedical Image Analysis
Basic knowledge of computer vision would be helpful.
W3 credits2G
227-0391-00 GMedical Image Analysis2 hrs
Tue13:15-15:00CAB G 11 »
E. Konukoglu, M. A. Reyes Aguirre
261-5113-00LComputational Challenges in Medical Genomics Information Restricted registration - show details
Number of participants limited to 20.
W2 credits2S
261-5113-00 SComputational Challenges in Medical Genomics2 hrs
Mon13:15-15:00CAB G 57 »
A. Kahles, G. Rätsch
261-5120-00LMachine Learning for Health Care Information Restricted registration - show details
Number of participants limited to 150.
W5 credits3P + 1A
261-5120-00 PMachine Learning for Health Care3 hrs
Thu15:00-18:00ER SA TZ »
15:15-18:00ETF C 1 »
G. Rätsch, J. Vogt, V. Boeva
261-5120-00 AMachine Learning for Health Care1 hrsG. Rätsch, J. Vogt, V. Boeva
262-0200-00LBayesian PhylodynamicsW4 credits2G + 2A
262-0200-00 GBayesian Phylodynamics
***ATTENTION: Starting with the lecture on March18, the Bayesian Phylodynamics lecture will be broadcasted using a Zoom videoconference. The lecturer will inform the students about the URL to participate in the online course***
2 hrs
Wed11:15-13:00BSB E 4 »
T. Stadler, T. Vaughan
262-0200-00 ABayesian Phylodynamics2 hrsT. Stadler, T. Vaughan
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