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EE-554: Automatic speech processing

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MICRO-455: Machine learning I

EE-566: Adaptation and learning

In this course, students learn to design and master algorithms and core concepts related to inference and learning from data and the foundations of adaptation and learning theories with applications.

MICRO-310(b): Signals and systems I (for SV)

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EE-612: Fundamentals in statistical pattern recognition

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MICRO-310(a): Signals and systems I (for MT)

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PHYS-512: Statistical physics of computation

The students understand tools from the statistical physics of disordered systems, and apply them to study computational and statistical problems in graph theory, discrete optimisation, inference and m

EE-452: Network machine learning

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EE-512: Applied biomedical signal processing

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DH-405: Foundations of digital humanities

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PHYS-754: Lecture series on scientific machine learning

This lecture presents ongoing work on how scientific questions can be tackled using machine learning. Machine learning enables extracting knowledge from data computationally and in an automatized way.