Search result: Course units in Autumn Semester 2019
Electrical Engineering and Information Technology Master  | ||||||
 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 https://www.ee.ethz.ch/studies/main-master/areas-of-specialisation.html. 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. | ||||||
| Advanced Core Courses Advanced core courses bring students to gain in-depth knowledge of the chosen specialization. They are MSc level only. | ||||||
| Number | Title | Type | ECTS | Hours | Lecturers | |
|---|---|---|---|---|---|---|
| 227-0423-00L | Neural Network Theory | W | 4 credits | 2V + 1U | H. Bölcskei, E. Riegler | |
| 227-0427-00L | Signal Analysis, Models, and Machine Learning | W | 6 credits | 4G | H.‑A. Loeliger | |
| 227-0447-00L | Image Analysis and Computer Vision | W | 6 credits | 3V + 1U | L. Van Gool, O. Göksel, E. Konukoglu | |
| 252-0535-00L | Advanced Machine Learning | W | 8 credits | 3V + 2U + 2A | J. M. Buhmann | |
| 263-3210-00L | Deep Learning | W | 5 credits | 2V + 1U + 1A | T. Hofmann | |
Page
1
of
1
