Search result: Course units in Spring Semester 2025
Electrical Engineering and Information Technology Master  | ||||||
 Master Studies (Programme Regulations 2018) | ||||||
| Track: 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 https://www.ee.ethz.ch/studies/main-master/areas-of-specialisation.html. The individual study plan is subject to the tutor's approval. | ||||||
| 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. Semester / Research Projects are not allowed in this category. A minimum of 40 credits must be obtained from specialization courses during the MSc EEIT. | ||||||
| Number | Title | Type | ECTS | Hours | Lecturers | |
|---|---|---|---|---|---|---|
| 151-0566-00L | Recursive Estimation | W | 4 credits | 2V + 1U | R. D'Andrea | |
| 227-0120-00L | Communication Networks | W | 6 credits | 4G | L. Vanbever | |
| 227-0147-00L | VLSI 2: From Netlist to Complete System on Chip  | W | 6 credits | 5G | F. K. Gürkaynak, L. Benini | |
| 227-0418-00L | Algebra and Error Correcting Codes | W | 6 credits | 4G | H.‑A. Loeliger | |
| 227-0150-00L | Systems-on-Chip for Data Analytics and Machine Learning | W | 6 credits | 4G | L. Benini, F. K. Gürkaynak | |
| 227-0155-00L | Machine Learning on Microcontrollers Registration in this class requires the permission of the instructors. | W | 6 credits | 4G | M. Magno, L. Benini | |
| 227-0422-00L | Deep Generative Models | W | 2 credits | 2V | E. Erdil | |
| 227-0424-00L | Model- and Learning-Based Inverse Problems in Imaging | W | 4 credits | 2V + 1P | V. Vishnevskiy | |
| 227-0432-00L | Learning, Classification and Compression | W | 4 credits | 2V + 1U | E. Riegler | |
| 227-0478-00L | Acoustics II Does not take place this semester. | W | 3 credits | 2G | ||
| 227-0558-00L | Principles of Distributed Computing | W | 7 credits | 2V + 2U + 2A | R. Wattenhofer, M. Fischer | |
| 227-0707-00L | Optimization Methods for Engineers | W | 3 credits | 2G | J. Smajic, G. Beccuti | |
| 227-0948-00L | Magnetic Resonance Imaging in Medicine | W | 4 credits | 3G | S. Kozerke | |
| 227-0973-00L | Translational Neuromodeling | W | 8 credits | 3V + 2U + 1A | K. Stephan | |
| 227-1032-00L | Neuromorphic Engineering II 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 | W | 6 credits | 5G | T. Delbrück, G. Indiveri, S.‑C. Liu, M. Payvand | |
| 252-0579-00L | 3D Vision | W | 5 credits | 3G + 1A | M. Pollefeys, D. B. Baráth | |
| 263-3710-00L | Machine Perception | W | 8 credits | 3V + 2U + 2A | M. Kaufmann, O. Hilliges, X. Wang | |
| 252-3900-00L | Big Data for Engineers This course is not intended for Computer Science and Data Science MSc students! | W | 6 credits | 2V + 2U + 1A | G. Fourny | |
| 263-5904-00L | Deep Learning for Computer Vision: Seminal Work The deadline for deregistering expires at the end of the first week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar. | W | 2 credits | 2S | Z. Bauer | |
| 401-3052-05L | Introduction to Graph Theory This is the first half of the course unit 401-3052-10L Graph Theory. Notice that at most one of the two course units 401-3052-05L Introduction to Graph Theory and 401-3052-10L Graph Theory can be recognised for credits. | W | 5 credits | 2V + 1U | B. Sudakov | |
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