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PHYS-101(k): General physics : mechanics

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BIO-212: Biological chemistry I

Biochemistry is a key discipline for the Life Sciences. Biological Chemistry I and II are two tightly interconnected courses that aim to describe and understand in molecular terms the processes that m

MATH-111(d): Linear Algebra

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MSE-326: Ceramic and colloidal processing

The course covers the production of ceramics and colloids from the basic scientific concepts and theories needed to understand the forming processes to the mechanisms and methods of sintering (firing)

COM-500: Statistical signal and data processing through applications

Building up on the basic concepts of sampling, filtering and Fourier transforms, we address stochastic modeling, spectral analysis, estimation and prediction, classification, and adaptive filtering, w

MATH-328: Algebraic geometry I - Curves

Algebraic geometry is the common language for many branches of modern research in mathematics. This course gives an introduction to this field by studying algebraic curves and their intersection theor

MICRO-534: Advanced MEMS & microsystems

In depth analysis of the operation principles and technology of advanced micro- and nanosystems. Familiarisation to their implementation into products and their applications.

PHYS-491: Magnetism in materials

The lectures will provide an introduction to magnetism in materials, covering fundamentals of spin and orbital degrees of freedom, interactions between moments and some typical ordering patterns. Sele

ME-301: Measurement techniques

Theoretical and practical course on experimental techniques for observation and measurement of physical variables such as force, strain, temperature, flow velocity, structural deformation and vibratio

ME-435: Aeroelasticity and fluid-structure interaction

La réponse statique et dynamique des systèmes couplés fluide-structure résultant de l'excitation indépendante, l'excitation induite par le mouvement, et l'excitation induite par les instabilités des f

CS-526: Learning theory

Machine learning and data analysis are becoming increasingly central in many sciences and applications. This course concentrates on the theoretical underpinnings of machine learning.