Search result: Course units in Autumn Semester 2020

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

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
Fundamentals at bachelor level, for master students who need to strengthen or refresh their background in the area.
227-0101-00LDiscrete-Time and Statistical Signal Processing Information W6 credits4GH.‑A. Loeliger
227-0105-00LIntroduction to Estimation and Machine Learning Restricted registration - show details W6 credits4GH.‑A. Loeliger
Advanced Core Courses
Advanced core courses bring students to gain in-depth knowledge of the chosen specialization. They are MSc level only.
227-0423-00LNeural Network Theory Information W4 credits2V + 1UH. Bölcskei
227-0427-00LSignal 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This course has been replaced by "Introduction to Estimation and Machine Learning" (autumn semester) and "Advanced Signal Analysis, Modeling, and Machine Learning" (spring semester).
W6 credits4GH.‑A. Loeliger
227-0447-00LImage Analysis and Computer Vision Information W6 credits3V + 1UL. Van Gool, E. Konukoglu, F. Yu
252-0535-00LAdvanced Machine Learning Information W10 credits3V + 2U + 4AJ. M. Buhmann, C. Cotrini Jimenez
263-3210-00LDeep Learning Information Restricted registration - show details W8 credits3V + 2U + 2AT. Hofmann
Specialisation Courses
These specialisation 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 specialisation courses during the MSc EEIT.
227-0116-00LVLSI I: From Architectures to VLSI Circuits and FPGAs Information W6 credits5GF. 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 credits3GM. Magno, L. Benini
227-0121-00LCommunication Systems Information W6 credits2V + 2UA. Wittneben
227-0225-00LLinear System TheoryW6 credits5GM. Colombino
227-0417-00LInformation Theory IW6 credits4GA. Lapidoth
227-0421-00LLearning in Deep Artificial and Biological Neuronal NetworksW4 credits3GB. Grewe
227-0445-10LMathematical Methods of Signal Processing Information W6 credits4GH. G. Feichtinger
227-0477-00LAcoustics IW6 credits4GK. Heutschi
263-5210-00LProbabilistic Artificial Intelligence Information Restricted registration - show details W8 credits3V + 2U + 2AA. Krause
401-0647-00LIntroduction to Mathematical Optimization Restricted registration - show details W5 credits2V + 1UD. Adjiashvili
401-3054-14LProbabilistic Methods in Combinatorics Information W6 credits2V + 1UB. Sudakov
401-3621-00LFundamentals of Mathematical Statistics Information W10 credits4V + 1US. van de Geer
401-3901-00LMathematical OptimizationW11 credits4V + 2UR. Zenklusen
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