Search result: Courses in Spring Semester 2021

Data Science Master Information
Core Courses
Data Analysis
Information and Learning
NumberTitleTypeECTSHoursLecturers
227-0434-10LMathematics of Information Information W8 credits3V + 2U + 2A
227-0434-10 VMathematics of Information3 hrs
Thu09-12HG D 3.2 »
H. Bölcskei
227-0434-10 UMathematics of Information2 hrs
Mon14-16HG D 3.2 »
H. Bölcskei
227-0434-10 AMathematics of Information2 hrsH. Bölcskei
Statistics
NumberTitleTypeECTSHoursLecturers
401-3632-00LComputational StatisticsW8 credits3V + 1U
401-3632-00 VComputational Statistics
Vorlesung im HG F 1 mit Videoübertragung ins HG F 3.
3 hrs
Thu14-16HG F 1 »
14-16HG F 3 »
Fri09-10HG F 1 »
09-10HG F 3 »
M. Mächler
401-3632-00 UComputational Statistics
A "Präsenzstunde" directly following the exercises will be offered Friday 11-12 in HG G 5.
1 hrs
Fri10-11HG G 5 »
M. Mächler
Data Management
NumberTitleTypeECTSHoursLecturers
261-5110-00LOptimization for Data Science Information W10 credits3V + 2U + 4A
261-5110-00 VOptimization for Data Science3 hrs
Mon13-14NO C 60 »
Tue10-12ETF C 1 »
B. Gärtner, D. Steurer, N. He
261-5110-00 UOptimization for Data Science2 hrs
Tue14-16HG D 5.2 »
14-16ML H 44 »
B. Gärtner, D. Steurer, N. He
261-5110-00 AOptimization for Data Science4 hrsB. Gärtner, D. Steurer, N. He
Core Electives
NumberTitleTypeECTSHoursLecturers
151-0566-00LRecursive Estimation Information W4 credits2V + 1U
151-0566-00 VRecursive Estimation
The lecture starts in the second week of the Semester.
2 hrs
Wed14-16HG F 1 »
R. D'Andrea
151-0566-00 URecursive Estimation
The exercise starts in the second week of the Semester.
1 hrs
Wed16-17HG F 1 »
R. D'Andrea
227-0150-00LSystems-on-Chip for Data Analytics and Machine Learning
Previously "Energy-Efficient Parallel Computing Systems for Data Analytics"
W6 credits4G
227-0150-00 GSystems-on-Chip for Data Analytics and Machine Learning4 hrs
Tue08-12ETZ E 9 »
L. Benini
227-0155-00LMachine Learning on Microcontrollers Restricted registration - show details
Number of participants limited to 40.
Registration in this class requires the permission of the instructors.
W6 credits3G
227-0155-00 GMachine Learning on Microcontrollers Special students and auditors need a special permission from the lecturers.
Permission from lecturers required for all students.
3 hrs
Mon13-16ETZ K 63 »
M. Magno, L. Benini
227-0224-00LStochastic SystemsW4 credits2V + 1U
227-0224-00 VStochastic Systems
Does not take place this semester.
Will be offered again in 2022.
2 hrsto be announced
227-0224-00 UStochastic Systems
Does not take place this semester.
Will be offered again in 2022.
1 hrsto be announced
227-0420-00LInformation Theory II Information W6 credits4G
227-0420-00 GInformation Theory II4 hrs
Thu14-18ETZ E 9 »
A. Lapidoth, S. M. Moser
227-0424-00LModel- and Learning-Based Inverse Problems in ImagingW4 credits2V + 1P
227-0424-00 VModel- and Learning-Based Inverse Problems in Imaging2 hrs
Mon14-16ETZ E 8 »
V. Vishnevskiy
227-0424-00 PModel- and Learning-Based Inverse Problems in Imaging1 hrs
Tue14-15ETZ D 61.1 »
14-15ETZ D 96.1 »
V. Vishnevskiy
227-0427-10LAdvanced Signal Analysis, Modeling, and Machine Learning Information W6 credits4G
227-0427-10 GAdvanced Signal Analysis, Modeling, and Machine Learning4 hrs
Fri14-18ML F 39 »
H.‑A. Loeliger
227-0432-00LLearning, Classification and Compression Information W4 credits2V + 1U
227-0432-00 VLearning, Classification and Compression2 hrs
Thu09-11IFW A 32.1 »
E. Riegler
227-0432-00 ULearning, Classification and Compression1 hrs
Thu11-12IFW A 32.1 »
E. Riegler
227-0558-00LPrinciples of Distributed Computing Information W7 credits2V + 2U + 2A
227-0558-00 VPrinciples of Distributed Computing2 hrs
Wed08-10CAB G 11 »
R. Wattenhofer, M. Ghaffari
227-0558-00 UPrinciples of Distributed Computing
In Gruppen
2 hrs
Wed14-16LFW C 11 »
16-18HG G 26.1 »
R. Wattenhofer, M. Ghaffari
227-0558-00 APrinciples of Distributed Computing
No presence required.
Creative task outside the regular weekly exercises.
2 hrsR. Wattenhofer, M. Ghaffari
227-0560-00LDeep Learning for Autonomous Driving Information Restricted registration - show details
Registration in this class requires the permission of the instructors.
Class size will be limited to 80 students.
Please send an email to Dengxin Dai <dai@vision.ee.ethz.ch> about your courses/projects that are related to machine learning, computer vision, and Robotics.
W6 credits3V + 2P
227-0560-00 VDeep Learning for Autonomous Driving Special students and auditors need a special permission from the lecturers.
Permission from lecturers required for all students.
3 hrs
Fri13-16LFO C 13 »
D. Dai, A. Liniger
227-0560-00 PDeep Learning for Autonomous Driving Special students and auditors need a special permission from the lecturers.
Permission from lecturers required for all students.
2 hrs
Fri10-12ETZ D 61.1 »
10-12ETZ D 61.2 »
D. Dai, A. Liniger
252-0211-00LInformation Security Information W8 credits4V + 3U
252-0211-00 VInformation Security4 hrs
Thu14-16CAB G 61 »
Fri14-16CAB G 61 »
D. Basin, S. Capkun
252-0211-00 UInformation Security3 hrs
Wed16-19HG F 26.5 »
Thu16-19CAB G 61 »
D. Basin, S. Capkun
252-0526-00LStatistical Learning Theory Information W8 credits3V + 2U + 2A
252-0526-00 VStatistical Learning Theory3 hrs
Mon14-16HG G 3 »
Tue17-18HG F 5 »
J. M. Buhmann, C. Cotrini Jimenez
252-0526-00 UStatistical Learning Theory2 hrs
Mon16-18HG G 3 »
J. M. Buhmann, C. Cotrini Jimenez
252-0526-00 AStatistical Learning Theory2 hrsJ. M. Buhmann, C. Cotrini Jimenez
252-0538-00LShape Modeling and Geometry Processing Information W8 credits2V + 1U + 4A
252-0538-00 VShape Modeling and Geometry Processing2 hrs
Wed10-12CAB G 51 »
O. Sorkine Hornung
252-0538-00 UShape Modeling and Geometry Processing1 hrs
Fri11-12CAB G 56 »
O. Sorkine Hornung
252-0538-00 AShape Modeling and Geometry Processing4 hrsO. Sorkine Hornung
252-0579-00L3D Vision Information W5 credits3G + 1A
252-0579-00 G3D Vision3 hrs
Mon09-12CAB G 51 »
M. Pollefeys, V. Larsson
252-0579-00 A3D Vision1 hrsM. Pollefeys, V. Larsson
252-3005-00LNatural Language Processing Information Restricted registration - show details
Number of participants limited to 400.
W5 credits2V + 1U + 1A
252-3005-00 VNatural Language Processing2 hrs
Wed12-14HG E 7 »
R. Cotterell
252-3005-00 UNatural Language Processing1 hrs
Thu17-18CAB G 11 »
Fri11-12CAB G 11 »
R. Cotterell
252-3005-00 ANatural Language Processing1 hrsR. Cotterell
261-5130-00LResearch in Data Science Restricted registration - show details
Only for Data Science MSc.
W6 credits13A
261-5130-00 AResearch in Data Science180s hrsProfessors
263-0007-00LAdvanced Systems Lab Information Restricted registration - show details
Only for master students, otherwise a special permission by the study administration of D-INFK is required.
W8 credits3V + 2U + 2A
263-0007-00 VAdvanced Systems Lab Special students and auditors need a special permission from the lecturers.3 hrs
Mon10-12HG F 3 »
Thu09-10HG F 3 »
M. Püschel, C. Zhang
263-0007-00 UAdvanced Systems Lab2 hrs
Wed14-16ETF C 1 »
M. Püschel, C. Zhang
263-0007-00 AAdvanced Systems Lab
Project Work, no fixed presence required.
2 hrsM. Püschel, C. Zhang
263-0008-00LComputational Intelligence Lab Information
Only for master students, otherwise a special permission by the study administration of D-INFK is required.
W8 credits2V + 2U + 3A
263-0008-00 VComputational Intelligence Lab
The lecturers will communicate the exact lesson times of ONLINE courses.
2 hrs
Fri10-12ON LI NE »
T. Hofmann
263-0008-00 UComputational Intelligence Lab
The lecturers will communicate the exact lesson times of ONLINE courses.
2 hrs
Thu14-16ON LI NE »
Fri16-18ON LI NE »
T. Hofmann
263-0008-00 AComputational Intelligence Lab
No presence required.
3 hrsT. Hofmann
263-2925-00LProgram Analysis for System Security and Reliability Information W7 credits2V + 1U + 3A
263-2925-00 VProgram Analysis for System Security and Reliability2 hrs
Tue16-18CAB G 51 »
M. Vechev
263-2925-00 UProgram Analysis for System Security and Reliability1 hrs
Thu13-14CAB G 51 »
M. Vechev
263-2925-00 AProgram Analysis for System Security and Reliability3 hrsM. Vechev
263-3710-00LMachine Perception Information Restricted registration - show details
Number of participants limited to 200.
W8 credits3V + 2U + 2A
263-3710-00 VMachine Perception3 hrs
Wed13-14HG F 1 »
Thu12-14HG E 5 »
O. Hilliges, S. Tang
263-3710-00 UMachine Perception2 hrs
Thu14-16CAB G 11 »
Fri14-16CAB G 11 »
O. Hilliges, S. Tang
263-3710-00 AMachine Perception2 hrsO. Hilliges, S. Tang
263-3855-00LCloud Computing Architecture Information W9 credits3V + 2U + 3A
263-3855-00 VCloud Computing Architecture3 hrs
Tue11-12CAB G 61 »
Wed12-14CAB G 61 »
G. Alonso, A. Klimovic
263-3855-00 UCloud Computing Architecture2 hrs
Wed16-18CAB G 11 »
G. Alonso, A. Klimovic
263-3855-00 ACloud Computing Architecture3 hrsG. Alonso, A. Klimovic
263-4400-00LAdvanced Graph Algorithms and Optimization Information W8 credits3V + 1U + 3A
263-4400-00 VAdvanced Graph Algorithms and Optimization3 hrs
Mon10-11ML F 38 »
Tue16-18ML F 38 »
R. Kyng, M. Probst
263-4400-00 UAdvanced Graph Algorithms and Optimization1 hrs
Thu15-16ML F 38 »
R. Kyng, M. Probst
263-4400-00 AAdvanced Graph Algorithms and Optimization3 hrsR. Kyng, M. Probst
263-5000-00LComputational Semantics for Natural Language Processing Information Restricted registration - show details
Limited number of participants: 80. Last cancellation/deregistration date for this graded semester performance: Friday, 26 March 2021! Please note that after that date no deregistration will be accepted and the course will be considered as "fail".
W6 credits2V + 1U + 2A
263-5000-00 VComputational Semantics for Natural Language Processing2 hrs
Thu10-12CAB G 51 »
M. Sachan
263-5000-00 UComputational Semantics for Natural Language Processing1 hrs
Thu15-16CAB G 59 »
M. Sachan
263-5000-00 AComputational Semantics for Natural Language Processing2 hrsM. Sachan
263-5300-00LGuarantees for Machine Learning Information Restricted registration - show details
Number of participants limited to 30.

Last cancellation/deregistration date for this graded semester performance: 17 March 2021! Please note that after that date no deregistration will be accepted and a "no show" will appear on your transcript.
W7 credits3G + 3A
263-5300-00 GGuarantees for Machine Learning3 hrs
Thu12-14CAB G 59 »
Fri12-13CAB G 59 »
F. Yang
263-5300-00 AGuarantees for Machine Learning3 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
Mon16-18HG F 1 »
R. Hiptmair
401-0674-00 UNumerical Methods for Partial Differential Equations
Groups are selected in myStudies.
2 hrs
Fri10-12ETZ E 8 »
10-12HG D 1.1 »
10-12HG G 3 »
11-13ETZ 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
401-3052-10LGraph Theory Information W10 credits4V + 1U
401-3052-10 VGraph Theory4 hrs
Wed10-12HG E 5 »
Thu10-12HG F 3 »
B. Sudakov
401-3052-10 UGraph Theory1 hrs
Thu16-17CAB G 52 »
16-17CAB G 56 »
16-17HG E 33.5 »
17-18HG E 33.5 »
29.04.18-19HG D 1.1 »
B. Sudakov
401-3602-00LApplied Stochastic Processes Information W8 credits3V + 1U
401-3602-00 VApplied Stochastic Processes3 hrs
Tue09-12IFW A 36 »
V. Tassion
401-3602-00 UApplied Stochastic Processes
Groups are selected in myStudies.
Thu 9-10 or Thu 12-13
1 hrs
Wed13-14HG E 33.1 »
Thu09-10LFW C 1 »
12-13HG G 26.5 »
V. Tassion
401-4632-15LCausality Information W4 credits2G
401-4632-15 GCausality2 hrs
Wed10-12HG E 1.1 »
C. Heinze-Deml
401-4656-21LDeep Learning in Scientific Computing Restricted registration - show details
Aimed at students in a Master's Programme in Mathematics, Engineering and Physics.
W6 credits2V + 1U
401-4656-21 VDeep Learning in Scientific Computing2 hrs
Mon14-16HG F 5 »
S. Mishra
401-4656-21 UDeep Learning in Scientific Computing1 hrs
Thu13-14ML H 44 »
S. Mishra
401-4944-20LMathematics of Data ScienceW8 credits4G
401-4944-20 GMathematics of Data Science
Does not take place this semester.
Planned to take place again in the Autumn Semester 2021.
4 hrsA. Bandeira
401-6102-00LMultivariate StatisticsW4 credits2G
401-6102-00 GMultivariate Statistics
Does not take place this semester.
By way of exception the course does not take place in the Spring Semester 2021.
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
Mon14-16HPV G 5 »
P. Kammerlander
402-0448-01 UQuantum Information Processing I: Concepts1 hrs
Mon16-17HCI H 8.1 »
16-17HCI J 4 »
16-17HIL E 10.1 »
16-17HPV G 5 »
P. Kammerlander
701-0104-00LStatistical Modelling of Spatial DataW3 credits2G
701-0104-00 GStatistical Modelling of Spatial Data2 hrs
Wed08-10CHN F 46 »
A. J. Papritz