Search result: Course units in Spring Semester 2021

Electrical Engineering and Information Technology Master Information
Master Studies (Programme Regulations 2018)
Signal Processing and Machine Learning
The core courses and specialization courses below are a selection for students who wish to specialize in the area of "Signal Processing and Machine Learning ", see Link.

The individual study plan is subject to the tutor's approval.
Core Courses
These core courses are particularly recommended for the field of "Signal Processing and Machine Learning".
You may choose core courses form other fields in agreement with your tutor.

A minimum of 24 credits must be obtained from core courses during the MSc EEIT.
Foundation Core Courses
NumberTitleTypeECTSHoursLecturers
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, F. Yang
Advanced Core Courses
NumberTitleTypeECTSHoursLecturers
227-0427-10LAdvanced Signal Analysis, Modeling, and Machine Learning Information W6 credits4GH.‑A. Loeliger
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
401-4944-20LMathematics of Data Science
Does not take place this semester.
W8 credits4GA. Bandeira
Specialization Courses
These specialization courses are particularly recommended for the area of "Signal Processing and Machine Learning", but you are free to choose courses from any other field in agreement with your tutor.

A minimum of 40 credits must be obtained from specialization courses during the MSc EEIT.
NumberTitleTypeECTSHoursLecturers
227-0120-00LCommunication Networks Information W6 credits4GL. Vanbever
227-0147-00LVLSI II: Design of Very Large Scale Integration Circuits Information W6 credits5GF. K. Gürkaynak, L. Benini
227-0418-00LAlgebra and Error Correcting Codes Information W6 credits4GH.‑A. Loeliger
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
Number of participants limited to 40.
Registration in this class requires the permission of the instructors.
W6 credits3GM. Magno, L. Benini
227-0424-00LModel- and Learning-Based Inverse Problems in ImagingW4 credits2V + 1PV. Vishnevskiy
227-0432-00LLearning, Classification and Compression Information W4 credits2V + 1UE. Riegler
227-0436-00LDigital Communication and Signal Processing
Does not take place this semester.
W6 credits2V + 2UA. Wittneben
227-0478-00LAcoustics II Information W6 credits4GK. Heutschi, R. Pieren
227-0449-00LSeminar in Biomedical Image ComputingW1 credit2SE. Konukoglu, B. Menze, M. A. Reyes Aguirre
227-0558-00LPrinciples of Distributed Computing Information W7 credits2V + 2U + 2AR. 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 <Link> about your courses/projects that are related to machine learning, computer vision, and Robotics.
W6 credits3V + 2PD. Dai, A. Liniger
227-0707-00LOptimization Methods for EngineersW3 credits2GJ. Smajic
227-0948-00LMagnetic Resonance Imaging in MedicineW4 credits3GS. Kozerke, M. Weiger Senften
227-0973-00LTranslational NeuromodelingW8 credits3V + 2U + 1AK. Stephan
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