Search result: Course units 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
Core Subjects
NumberTitleTypeECTSHoursLecturers
227-0434-10LMathematics of Information Information W8 credits3V + 2U + 2AH. Bölcskei
227-0391-00LMedical Image Analysis
Basic knowledge of computer vision would be helpful.
W3 credits2GE. Konukoglu, M. A. Reyes Aguirre
252-0220-00LIntroduction to Machine Learning Information Restricted registration - show details
Limited number of participants. Preference is given to students in programmes in which the course is being offered. All other students will be waitlisted. Please do not contact Prof. Krause for any questions in this regard. If necessary, please contact Link
W8 credits4V + 2U + 1AA. Krause
401-4944-20LMathematics of Data ScienceW8 credits4GA. Bandeira
Recommended Subjects
NumberTitleTypeECTSHoursLecturers
227-0147-00LVLSI II: Design of Very Large Scale Integration Circuits Information W6 credits5GF. 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 credits4GL. 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 + 2AM. Magno, L. Benini
227-0418-00LAlgebra and Error Correcting Codes Information W6 credits4GH.‑A. Loeliger
227-0436-00LDigital Communication and Signal ProcessingW6 credits2V + 2UA. Wittneben
227-0478-00LAcoustics II Information W6 credits4GK. 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 + 2PD. Dai, A. Liniger
227-0707-00LOptimization Methods for EngineersW3 credits2GP. Leuchtmann
227-0948-00LMagnetic Resonance Imaging in MedicineW4 credits3GS. 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 credits5GS.‑C. Liu, T. Delbrück, G. Indiveri
151-0566-00LRecursive Estimation Information W4 credits2V + 1UR. D'Andrea
252-0526-00LStatistical Learning Theory Information W7 credits3V + 2U + 1AJ. M. Buhmann, C. Cotrini Jimenez
252-0579-00L3D Vision Information W5 credits3G + 1AM. Pollefeys, V. Larsson
227-0973-00LTranslational Neuromodeling Information W8 credits3V + 2U + 1AK. 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 credits2SM. 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 + 1AG. Fourny
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