CS-526: Learning theoryMachine learning and data analysis are becoming increasingly central in many sciences and applications. This course concentrates on the theoretical underpinnings of machine learning.
PHYS-314: Quantum physics IIThe aim of this course is to familiarize the student with the concepts, methods and consequences of quantum physics.
EE-334: Digital systems designStudents will acquire basic knowledge about methodologies and tools for the design, optimization, and verification of custom digital systems/hardware.
They learn how to design synchronous digital cir
BIO-341: Dynamical systems in biologyLife is non-linear. This course introduces dynamical systems as a technique for modelling simple biological processes. The emphasis is on the qualitative and numerical analysis of non-linear dynamical
CS-413: Computational photographyThe students will gain the theoretical knowledge in computational photography, which allows recording and processing a richer visual experience than traditional digital imaging. They will also execute
MATH-404: Functional analysis IIWe introduce locally convex vector spaces. As an example we treat the space of test functions and the space of distributions. In the second part of the course, we discuss differential calculus in Bana
CS-487: Industrial automationThis course consists of two parts:
- architecture of automation systems, hands-on lab
- dependable systems and handling of faults and failures in real-time systems, including fault-tolerant computin
MATH-431: Theory of stochastic calculusIntroduction to the mathematical theory of stochastic calculus: construction of stochastic Ito integral, proof of Ito formula, introduction to stochastic differential equations, Girsanov theorem and F
