Search result: Courses in Autumn Semester 2017

Data Science Master Information
Core Courses
Data Analysis
Information and Learning
NumberTitleTypeECTSHoursLecturers
252-0535-00LMachine Learning Information W8 credits3V + 2U + 2A
252-0535-00 VMachine Learning
Vorlesung:
Donnerstag im ML D 28 mit Videoübertragung im ML E 12
Freitag im HG F 1 mit Videoübertragung im HG F 3
3 hrs
Thu14:15-15:00ML D 28 »
14:15-15:00ML E 12 »
Fri08:15-10:00HG F 1 »
08:15-10:00HG F 3 »
J. M. Buhmann
252-0535-00 UMachine Learning2 hrs
Wed13:15-15:00CAB G 61 »
15:15-17:00CAB G 61 »
Thu15:15-17:00CAB G 51 »
Fri13:15-15:00CAB G 61 »
J. M. Buhmann
252-0535-00 AMachine Learning
Project Work, no fixed presence required.
2 hrsJ. M. Buhmann
Statistics
NumberTitleTypeECTSHoursLecturers
401-3621-00LFundamentals of Mathematical Statistics Information W10 credits4V + 1U
401-3621-00 VFundamentals of Mathematical Statistics4 hrs
Wed10:15-12:00HG E 1.1 »
Fri08:15-10:00HG E 1.1 »
S. van de Geer
401-3621-00 UFundamentals of Mathematical Statistics1 hrs
Tue12:15-13:00HG E 1.1 »
S. van de Geer
Data Management
NumberTitleTypeECTSHoursLecturers
263-3010-00LBig Data Information Restricted registration - show details W8 credits3V + 2U + 2A
263-3010-00 VBig Data3 hrs
Tue10:15-12:00HG E 5 »
Wed09:15-10:00HG E 5 »
G. Fourny
263-3010-00 UBig Data2 hrs
Wed13:15-15:00CHN D 46 »
13:15-15:00CHN G 46 »
13:15-15:00HG F 26.3 »
13:15-15:00ML F 36 »
Fri13:15-15:00CAB G 52 »
13:15-15:00CAB G 56 »
G. Fourny
263-3010-00 ABig Data
Individual work to get hands-on experience with the technologies covered, no fixed presence required.
2 hrsG. Fourny
Core Electives
NumberTitleTypeECTSHoursLecturers
252-0417-00LRandomized Algorithms and Probabilistic MethodsW8 credits3V + 2U + 2A
252-0417-00 VRandomized Algorithms and Probabilistic Methods3 hrs
Tue13:15-14:00CAB G 51 »
Thu08:15-10:00CAB G 51 »
A. Steger, E. Welzl
252-0417-00 URandomized Algorithms and Probabilistic Methods2 hrs
Tue16:15-18:00CAB G 51 »
A. Steger, E. Welzl
252-0417-00 ARandomized Algorithms and Probabilistic Methods
Project Work, no fixed presence required.
2 hrsA. Steger, E. Welzl
252-1407-00LAlgorithmic Game Theory Information W7 credits3V + 2U + 1A
252-1407-00 VAlgorithmic Game Theory3 hrs
Mon09:15-12:00CAB G 51 »
P. Penna
252-1407-00 UAlgorithmic Game Theory2 hrs
Mon15:15-17:00CAB G 56 »
15:15-17:00CAB G 59 »
15:15-17:00IFW C 33 »
P. Penna
252-1407-00 AAlgorithmic Game Theory
Project Work, no fixed presence required.
1 hrsP. Penna
252-1414-00LSystem Security Information W5 credits2V + 2U
252-1414-00 VSystem Security2 hrs
Mon10:15-12:00IFW A 36 »
S. Capkun, A. Perrig
252-1414-00 USystem Security2 hrs
Thu13:15-15:00HG D 3.2 »
S. Capkun, A. Perrig
263-0006-00LAlgorithms Lab
Only for master students, otherwise a special permission by the student administration of D-INFK is required.
W8 credits4P + 1A
263-0006-00 PAlgorithms Lab4 hrs
Mon17:15-19:00CAB H 56 »
17:15-19:00CAB H 57 »
17:15-19:00HG E 26.1 »
Wed17:15-19:00CAB G 61 »
A. Steger, E. Welzl, P. Widmayer
263-0006-00 AAlgorithms Lab
Project Work, no fixed presence required.
1 hrsA. Steger, E. Welzl, P. Widmayer
263-0007-00LAdvanced Systems Lab Information
Only for master students, otherwise a special permission by the student administration of D-INFK is required.
W8 credits4P + 1A
263-0007-00 PAdvanced Systems Lab4 hrs
Tue17:15-19:00CAB G 61 »
Thu17:15-19:00CAB G 52 »
17:15-19:00CAB G 56 »
17:15-19:00CHN D 42 »
17:15-19:00CHN D 44 »
17:15-19:00CHN D 46 »
21.09.17:15-19:00CAB G 61 »
28.09.17:15-19:00CAB G 61 »
05.10.17:15-19:00CAB G 61 »
G. Alonso
263-0007-00 AAdvanced Systems Lab
Project Work, no fixed presence required.
1 hrsG. Alonso
263-2400-00LReliable and Interpretable Artificial Intelligence Information W4 credits2V + 1U
263-2400-00 VReliable and Interpretable Artificial Intelligence2 hrs
Tue10:15-12:00HG E 3 »
19.09.10:15-12:00CAB G 59 »
26.09.10:15-12:00CAB G 59 »
M. Vechev
263-2400-00 UReliable and Interpretable Artificial Intelligence1 hrs
Tue14:15-15:00HG F 26.3 »
Wed11:15-12:00CAB G 59 »
M. Vechev
263-2800-00LDesign of Parallel and High-Performance Computing Information W7 credits3V + 2U + 1A
263-2800-00 VDesign of Parallel and High-Performance Computing3 hrs
Mon13:15-16:00LEE D 101 »
T. Hoefler, M. Püschel
263-2800-00 UDesign of Parallel and High-Performance Computing2 hrs
Thu13:15-15:00LEE D 101 »
T. Hoefler, M. Püschel
263-2800-00 ADesign of Parallel and High-Performance Computing
Project Work, no fixed presence required.
1 hrsT. Hoefler, M. Püschel
263-3210-00LDeep Learning Information Restricted registration - show details
Number of participants limited to 300.
W4 credits2V + 1U
263-3210-00 VDeep Learning2 hrs
Mon13:15-15:00ETF C 1 »
T. Hofmann
263-3210-00 UDeep Learning1 hrs
Mon15:15-16:00CAB G 51 »
16:15-17:00ML F 36 »
T. Hofmann
263-5210-00LProbabilistic Artificial Intelligence Information W4 credits2V + 1U
263-5210-00 VProbabilistic Artificial Intelligence
Am 22. und 29. September findet die Vorlesung in HG E 7 statt!

On September 22 and 29., the lecture will take place in room HG E 7.

Ab dem 06. Oktober findet die Vorlesung im HG E 7 statt mit Videoübertragung im HG E 3.
2 hrs
Fri10:15-12:00HG E 3 »
10:15-12:00HG E 7 »
A. Krause
263-5210-00 UProbabilistic Artificial Intelligence1 hrs
Fri13:15-14:00CHN C 14 »
14:15-15:00CHN C 14 »
A. Krause
263-5902-00LComputer Vision Information W6 credits3V + 1U + 1A
263-5902-00 VComputer Vision3 hrs
Wed13:15-16:00CHN C 14 »
L. Van Gool, V. Ferrari, A. Geiger
263-5902-00 UComputer Vision1 hrs
Thu15:15-16:00CHN C 14 »
L. Van Gool, V. Ferrari, A. Geiger
263-5902-00 AComputer Vision1 hrsL. Van Gool, V. Ferrari, A. Geiger
401-0625-01LApplied Analysis of Variance and Experimental Design Information W5 credits2V + 1U
401-0625-01 VApplied Analysis of Variance and Experimental Design2 hrs
Mon13:15-15:00HG G 5 »
L. Meier
401-0625-01 UApplied Analysis of Variance and Experimental Design
Mon 15-17 might not work for all different programmes where this course is offered. On sufficient demand, other slots for the exercise sessions can be offered.
1 hrs
Mon/2w15:15-17:00HG E 1.1 »
L. Meier
401-3601-00LProbability Theory
At most one of the three course units (Bachelor Core Courses)
401-3461-00L Functional Analysis I
401-3531-00L Differential Geometry I
401-3601-00L Probability Theory
can be recognised for the Master's degree in Mathematics or Applied Mathematics.
W10 credits4V + 1U
401-3601-00 VProbability Theory4 hrs
Tue10:15-12:00HG G 3 »
Thu10:15-12:00HG G 3 »
A.‑S. Sznitman
401-3601-00 UProbability Theory
Tue 13-14 or Tue 14-15 starting in the second week of the semester.
1 hrs
Tue13:15-14:00HG F 26.5 »
13:15-14:00ML H 41.1 »
14:15-15:00HG F 26.5 »
14:15-15:00ML H 41.1 »
A.‑S. Sznitman
401-3901-00LMathematical Optimization Information W11 credits4V + 2U
401-3901-00 VMathematical Optimization4 hrs
Mon13:15-15:00HG E 1.1 »
Thu10:15-12:00HG D 5.2 »
R. Weismantel
401-3901-00 UMathematical Optimization2 hrs
Fri10:15-12:00HG E 1.1 »
R. Weismantel
401-4619-67LAdvanced Topics in Computational StatisticsW4 credits2V
401-4619-00 VAdvanced Topics in Computational Statistics2 hrs
Thu08:15-10:00HG D 7.1 »
21.09.08:15-10:00HG E 33.3 »
N. Meinshausen
227-0101-00LDiscrete-Time and Statistical Signal ProcessingW6 credits4G
227-0101-00 GDiscrete-Time and Statistical Signal Processing4 hrs
Tue13:15-17:00ETF C 1 »
H.‑A. Loeliger
227-0417-00LInformation Theory IW6 credits4G
227-0417-00 GInformation Theory I4 hrs
Wed13:15-17:00ETF E 1 »
20.09.13:15-17:00ETZ E 9 »
27.09.13:15-17:00ETZ E 9 »
A. Lapidoth
227-0427-00LSignal and Information Processing: Modeling, Filtering, LearningW6 credits4G
227-0427-00 GSignal and Information Processing: Modeling, Filtering, Learning4 hrs
Fri08:15-12:00CHN C 14 »
H.‑A. Loeliger
  •  Page  1  of  3 Next page Last page     All