Search result: Courses in Spring Semester 2020

Electrical Engineering and Information Technology Master Information
Master Studies (Programme Regulations 2008)
Major Courses
A total of 42 CP must be achieved form courses during the Master Program. The individual study plan is subject to the tutor's approval.
Signal Processing and Machine Learning
Recommended Subjects
NumberTitleTypeECTSHoursLecturers
227-0147-00LVLSI II: Design of Very Large Scale Integration Circuits Information W6 credits5G
227-0147-00 GVLSI II: Design of Very Large Scale Integration Circuits
Vorlesung: Di 13-15
Übungen: Mi 9-12
5 hrs
Tue13-15LFW B 1 »
Wed09-12ETZ D 61.1 »
09-12ETZ D 96.1 »
F. K. Gürkaynak, L. Benini
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
Registration in this class requires the permission of the instructors. Class size will be limited to 30.
Preference is given to students in the MSc EEIT.
W6 credits3G + 2A
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
227-0155-00 AMachine Learning on Microcontrollers Special students and auditors need a special permission from the lecturers.
Permission from lecturers required for all students.
2 hrsM. Magno, L. Benini
227-0418-00LAlgebra and Error Correcting Codes Information W6 credits4G
227-0418-00 GAlgebra and Error Correcting Codes4 hrs
Tue13-17ETZ E 9 »
H.‑A. Loeliger
227-0436-00LDigital Communication and Signal ProcessingW6 credits2V + 2U
227-0436-00 VDigital Communication and Signal Processing2 hrs
Wed10-12ETZ H 91 »
A. Wittneben
227-0436-00 UDigital Communication and Signal Processing2 hrs
Wed08-10ETZ H 91 »
A. Wittneben
227-0478-00LAcoustics II Information W6 credits4G
227-0478-00 GAcoustics II4 hrs
Mon13-17ETZ E 7 »
K. Heutschi
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.
Preference is given to EEIT, INF and RSC students.
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
227-0707-00LOptimization Methods for EngineersW3 credits2G
227-0707-00 GOptimization Methods for Engineers2 hrs
Thu10-12CHN C 14 »
10-12ER SA TZ »
P. Leuchtmann
227-0948-00LMagnetic Resonance Imaging in MedicineW4 credits3G
227-0948-00 GMagnetic Resonance Imaging in Medicine3 hrs
Wed13-16CAB G 11 »
13-16ER SA TZ »
S. Kozerke, M. Weiger Senften
227-1032-00LNeuromorphic Engineering II Information
Information for UZH students:
Enrolment to this course unit only possible at ETH. No enrolment to module INI405 at UZH.

Please mind the ETH enrolment deadlines for UZH students: Link
W6 credits5G
227-1032-00 GNeuromorphic Engineering II
**together with University of Zurich**
More information at: Link

Vorlesung: 13-15
Übungen: 15-18
5 hrs
Tue13-15Y55 G 20 »
15-18Y35 E 30 »
S.‑C. Liu, T. Delbrück, G. Indiveri
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
Wed13-15ER SA TZ »
13-15HG F 1 »
R. D'Andrea
151-0566-00 URecursive Estimation
The exercise starts in the second week of the Semester.
1 hrs
Wed15-16ER SA TZ »
15-16HG F 1 »
R. D'Andrea
252-0526-00LStatistical Learning Theory Information W7 credits3V + 2U + 1A
252-0526-00 VStatistical Learning Theory3 hrs
Mon14-16ER SA TZ »
14-16HG G 3 »
Tue17-18ER SA TZ »
17-18HG G 3 »
J. M. Buhmann, C. Cotrini Jimenez
252-0526-00 UStatistical Learning Theory2 hrs
Mon16-18ER SA TZ »
16-18HG G 3 »
J. M. Buhmann, C. Cotrini Jimenez
252-0526-00 AStatistical Learning Theory1 hrsJ. M. Buhmann, C. Cotrini Jimenez
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
227-0973-00LTranslational Neuromodeling Information W8 credits3V + 2U + 1A
227-0973-00 VTranslational Neuromodeling3 hrs
Tue09-12HG G 26.1 »
K. Stephan
227-0973-00 UTranslational Neuromodeling2 hrs
Fri14-16ETZ E 6 »
K. Stephan
227-0973-00 ATranslational Neuromodeling
No presence required.
Creative work on a self-chosen project outside the regular weekly exercises.
1 hrsK. Stephan
263-5904-00LDeep Learning for Computer Vision: Seminal Work Information Restricted registration - show details
Number of participants limited to 24.

The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar.
W2 credits2S
263-5904-00 SDeep Learning for Computer Vision: Seminal Work2 hrs
Mon15-17CAB G 57 »
M. R. Oswald, Z. Cui
252-3900-00LBig Data for Engineers Information
This course is not intended for Computer Science and Data Science MSc students!
W6 credits2V + 2U + 1A
252-3900-00 VBig Data for Engineers2 hrs
Tue10-12ER SA TZ »
10-12HG G 5 »
G. Fourny
252-3900-00 UBig Data for Engineers
Groups are selected in myStudies.
2 hrs
Wed14-16CAB G 57 »
15-17ML H 34.3 »
15-17NO C 44 »
16-18NO D 11 »
Fri15-17CAB G 56 »
15-17CAB G 57 »
G. Fourny
252-3900-00 ABig Data for Engineers1 hrsG. Fourny
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
Wed08-10CAB G 51 »
F. Yang
263-5300-00 AGuarantees for Machine Learning2 hrsF. Yang
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