Search result: Courses in Autumn Semester 2020

Electrical Engineering and Information Technology Master Information
Master Studies (Programme Regulations 2008)
Major Courses
A total of 42 CP must be achieved during the Master Programme. The individual study plan is subject to the tutor's approval.
Signal Processing and Machine Learning
Core Subjects
NumberTitleTypeECTSHoursLecturers
227-0105-00LIntroduction to Estimation and Machine Learning Restricted registration - show details W6 credits4G
227-0105-00 GIntroduction to Estimation and Machine Learning Special students and auditors need a special permission from the lecturers.
The lecturers will communicate the exact lesson times of ONLINE courses.
4 hrs
Fri14:00-18:00ON LI NE »
H.‑A. Loeliger
227-0423-00LNeural Network Theory Information W4 credits2V + 1U
227-0423-00 VNeural Network Theory
«Hybrid».
Up to 150 students can attend the course on-site. Further information will be announced to enrolled students by e-mail in the week before the semester starts.

The first lecture is on 21.9.
2 hrs
Mon10:15-12:00ETF C 1 »
H. Bölcskei
227-0423-00 UNeural Network Theory
«Hybrid».
Up to 150 students can attend the course on-site. Further information will be announced to enrolled students by e-mail in the week before the semester starts.

The first lecture is on 21.9.
1 hrs
Mon12:15-13:00ETF C 1 »
H. Bölcskei
227-0427-00LSignal Analysis, Models, and Machine Learning
This course has been replaced by "Introduction to Estimation and Machine Learning" (autumn semester) and "Advanced Signal Analysis, Modeling, and Machine Learning" (spring semester).
W6 credits4G
227-0427-00 GSignal Analysis, Models, and Machine Learning
Does not take place this semester.
This course has been replaced by "Introduction to Estimation and Machine Learning" (autumn semester) and "Advanced Signal Analysis, Modeling, and Machine Learning" (spring semester)
4 hrsH.‑A. Loeliger
227-0447-00LImage Analysis and Computer Vision Information W6 credits3V + 1U
227-0447-00 VImage Analysis and Computer Vision
The lecturers will communicate the exact lesson times of ONLINE courses.
3 hrs
Thu14:00-17:00ON LI NE »
L. Van Gool, E. Konukoglu, F. Yu
227-0447-00 UImage Analysis and Computer Vision
The lecturers will communicate the exact lesson times of ONLINE courses.
1 hrs
Thu17:00-18:00ON LI NE »
L. Van Gool, E. Konukoglu
252-0535-00LAdvanced Machine Learning Information W10 credits3V + 2U + 4A
252-0535-00 VAdvanced Machine Learning
The lectures will mostly be given in a lecture hall with limited attendance (at most 50% of lecture hall capacity). It will be possible to join remotely via zoom with acccess to slides, whiteboard, and speaker camera. Students can interact, e.g. ask questions, physically as well as digitally. The lectures will be recorded via zoom’s recording functionality.
3 hrs
Thu15:15-16:00ETA F 5 »
Fri08:15-10:00ETA F 5 »
J. M. Buhmann, C. Cotrini Jimenez
252-0535-00 UAdvanced Machine Learning2 hrs
Wed14:15-16:00CAB G 61 »
16:15-18:00CAB G 61 »
Thu16:15-18:00ML F 34 »
Fri14:15-16:00CAB G 61 »
J. M. Buhmann, C. Cotrini Jimenez
252-0535-00 AAdvanced Machine Learning
Project Work, no fixed presence required.
4 hrsJ. M. Buhmann, C. Cotrini Jimenez
Recommended Subjects
NumberTitleTypeECTSHoursLecturers
227-0101-00LDiscrete-Time and Statistical Signal Processing Information W6 credits4G
227-0101-00 GDiscrete-Time and Statistical Signal Processing
The lecturers will communicate the exact lesson times of ONLINE courses.
4 hrs
Tue14:00-18:00ON LI NE »
H.‑A. Loeliger
227-0116-00LVLSI I: From Architectures to VLSI Circuits and FPGAs Information W6 credits5G
227-0116-00 GVLSI I: From Architectures to VLSI Circuits and FPGAs
Lecture: Tue 8 - 10 h
Execises: Wed 13 - 16 h or Thu 09 - 12 h
The lecturers will communicate the exact lesson times of ONLINE courses.
5 hrs
Tue08:00-10:00ON LI NE »
Wed13:15-16:00ETZ D 61.1 »
13:15-16:00ETZ D 61.2 »
13:15-16:00ETZ D 96.1 »
Thu09:15-12:00ETZ D 61.1 »
09:15-12:00ETZ D 61.2 »
09:15-12:00ETZ D 96.1 »
F. K. Gürkaynak, 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 16.
Preference is given to students in the MSc EEIT.
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.
All the lectures will be remote by zoom.

For exercises we will include a tutorial to install all the software at home.

The lab will be divided in 3 groups and students need physical assistance and can come in their dedicate time in ETZ K63.
3 hrs
Mon13:15-17:00ETZ K 63 »
M. Magno, L. Benini
227-0225-00LLinear System TheoryW6 credits5G
227-0225-00 GLinear System Theory
The lecturers will communicate the exact lesson times of ONLINE courses.
5 hrs
Mon09:00-12:00ON LI NE »
Wed10:00-12:00ON LI NE »
M. Colombino
227-0417-00LInformation Theory IW6 credits4G
227-0417-00 GInformation Theory I
Classroom teaching with lecture recording.
4 hrs
Wed14:15-18:00ETF C 1 »
A. Lapidoth
227-0421-00LLearning in Deep Artificial and Biological Neuronal NetworksW4 credits3G
227-0421-00 GLearning in Deep Artificial and Biological Neuronal Networks3 hrs
Wed09:15-12:00ML H 44 »
B. Grewe
227-0445-10LMathematical Methods of Signal Processing Information W6 credits4G
227-0445-10 GMathematical Methods of Signal Processing
Lecture start is on Tuesday, 6 October 2020.

Remote lecture on Tusdays 8-10h, per Zoom:
Meeting-ID: 994 133 7347
Kenncode: 530642

Remote exercise on Thursdays 14-16h, per Zoom.
Meeting-ID: 863 7709 0433
Kenncode: 170548

The lecturer will communicate the exact lesson times of ONLINE courses.
4 hrs
Tue08:00-10:00ON LI NE »
Thu14:00-16:00ON LI NE »
H. G. Feichtinger
227-0477-00LAcoustics IW6 credits4G
227-0477-00 GAcoustics I4 hrs
Mon14:15-18:00ETZ E 7 »
K. Heutschi
263-5210-00LProbabilistic Artificial Intelligence Information Restricted registration - show details W8 credits3V + 2U + 2A
263-5210-00 VProbabilistic Artificial Intelligence
The lectures will mostly be given in a lecture hall with limited attendance (at most 50% of lecture hall capacity). It will be possible to join remotely via zoom with acccess to slides, whiteboard, and speaker camera. Students can interact, e.g. ask questions, physically as well as digitally. The lectures will be recorded via zoom’s recording functionality.
3 hrs
Fri10:15-12:00ETA F 5 »
13:15-14:00ETA F 5 »
A. Krause
263-5210-00 UProbabilistic Artificial Intelligence2 hrs
Thu16:00-18:00ON LI NE »
A. Krause
263-5210-00 AProbabilistic Artificial Intelligence2 hrsA. Krause
401-0647-00LIntroduction to Mathematical Optimization Restricted registration - show details W5 credits2V + 1U
401-0647-00 VIntroduction to Mathematical Optimization
"Hybrid"
Online except in September/October 2020 for students in the Computational Science and Engineering Bachelor's Programme, where this course is mandatory.
Those students will be invited by the lecturer to the classroom teaching (Tue 16-18 ETH Zentrum campus).
As of November 2020 ONLINE for all students.
The lecturers will communicate the exact lesson times of ONLINE courses.
URL for live streaming: Link
2 hrs
Tue16:00-18:00ON LI NE »
D. Adjiashvili
401-0647-00 UIntroduction to Mathematical Optimization
Groups are selected in myStudies.
Wed 12-13 or Wed 16-17

The lecturers will communicate the exact lesson times of ONLINE courses.
1 hrs
Wed12:15-13:00HG D 1.2 »
16:00-17:00ON LI NE »
16:15-17:00HG D 1.2 »
D. Adjiashvili
401-3054-14LProbabilistic Methods in Combinatorics Information W6 credits2V + 1U
401-3054-14 VProbabilistic Methods in Combinatorics2 hrs
Wed10:15-12:00HG E 5 »
B. Sudakov
401-3054-14 UProbabilistic Methods in Combinatorics1 hrs
Mon15:15-16:00HG G 3 »
B. Sudakov
401-3621-00LFundamentals of Mathematical Statistics Information W10 credits4V + 1U
401-3621-00 VFundamentals of Mathematical Statistics
The lecturers will communicate the exact lesson times of ONLINE courses.
URL for live streaming: Link
4 hrs
Tue08:00-10:00ON LI NE »
Wed10:00-12:00ON LI NE »
S. van de Geer
401-3621-00 UFundamentals of Mathematical Statistics
The lecturers will communicate the exact lesson times of ONLINE courses.
1 hrs
Tue12:00-13:00ON LI NE »
S. van de Geer
401-3901-00LMathematical OptimizationW11 credits4V + 2U
401-3901-00 VMathematical Optimization
The lecturers will communicate the exact lesson times of ONLINE courses.
4 hrs
Mon14:00-16:00ON LI NE »
Thu10:00-12:00ON LI NE »
R. Zenklusen
401-3901-00 UMathematical Optimization
Groups are selected in myStudies.
Thu 14-16 or Fri 10-12 or Fr 12-14 or Fri 14-16 (depending on demand)

The lecturers will communicate the exact lesson times of ONLINE courses.
2 hrs
Thu14:00-16:00ON LI NE »
Fri10:15-12:00CAB G 51 »
12:15-14:00HG E 1.2 »
14:15-16:00HG G 26.1 »
R. Zenklusen
401-4619-67LAdvanced Topics in Computational StatisticsW4 credits2V
401-4619-00 VAdvanced Topics in Computational Statistics
Does not take place this semester.
2 hrsnot available
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