Suchergebnis:
Lerneinheiten im Herbstsemester 2022
Doktorat Informationstechnologie und Elektrotechnik Vertiefung Fachwissen A minimum of 12 ECTS credit points must be obtained during doctoral studies.
Nummer Titel Typ ECTS Umfang Dozierende 151-0371-00L Advanced Model Predictive Control Number of participants limited to 60.
W 4 KP 2V + 1U M. Zeilinger ,
A. Carron ,
L. Hewing ,
J. Köhler 227-0105-00L Introduction to Estimation and Machine Learning W 6 KP 4G H.‑A. Loeliger 227-0146-00L Analog-to-Digital Converters W 6 KP 2V + 2U T. Burger 227-0225-00L Linear System Theory W 6 KP 5G J. Lygeros ,
A. Tsiamis 227-0377-10L Physics of Failure and Reliability of Electronic Devices and Systems W 3 KP 2V I. Shorubalko ,
M. Held 227-0417-00L Information Theory I W 6 KP 4G A. Lapidoth 227-0579-00L Hardware Security W 7 KP 2V + 2U + 2A K. Razavi 227-0689-00L System Identification W 4 KP 2V + 1U R. Smith 227-0955-00L Seminar in Electromagnetics, Photonics and Terahertz W 3 KP 2S J. Leuthold 227-0974-00L TNU Colloquium W 0 KP 2K K. Stephan 252-0535-00L Advanced Machine Learning W 10 KP 3V + 2U + 4A J. M. Buhmann ,
C. Cotrini Jimenez 252-0417-00L Randomized Algorithms and Probabilistic Methods W 10 KP 3V + 2U + 4A A. Steger 327-2132-00L Multifunctional Ferroic Materials: Growth and Characterisation W 2 KP 2G M. Trassin 401-3055-64L Algebraic Methods in Combinatorics Findet dieses Semester nicht statt.
W 6 KP 2V + 1U B. Sudakov 401-5680-00L Foundations of Data Science Seminar Z 0 KP P. L. Bühlmann ,
A. Bandeira ,
H. Bölcskei ,
S. van de Geer ,
F. Yang
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