ENG-366: Signals, instruments and systemsThe goal of this course is to transmit knowledge in sensing, computing, communicating, and actuating for programmable
field instruments and, more generally, embedded systems. The student will be able
EE-411: Fundamentals of inference and learningThis is an introductory course in the theory of statistics, inference, and machine learning, with an emphasis on theoretical understanding & practical exercises. The course will combine, and alternat
DH-412: History and the digitalThe course presents a number of computational approaches & tools that can be used to study history. Drawing on case studies from the history of science & technology, the course also offers students th
CS-119(g): Information, Computation, CommunicationL'objectif de ce cours est d'initier les étudiants à la pensée algorithmique, de les familiariser avec les fondamentaux de
l'informatique et des communications et de développer une première compétence
MATH-459: Numerical methods for conservation lawsIntroduction to the development, analysis, and application of computational methods for solving conservation laws with an emphasis on finite volume, limiter based schemes, high-order essentially non-o
MSE-422: Advanced metallurgyThis course covers the metallurgy, processing and properties of modern high-performance metals and alloys (e.g. advanced steels, Ni-base, Ti-base, High Entropy Alloys etc.). In addition, the principle
BIOENG-320: Synthetic biologyThis advanced Bachelor/Master level course will cover fundamentals and approaches at the interface of biology, chemistry, engineering and computer science for diverse fields of synthetic biology. This
MATH-403: Randomized matrix computationsThis course is concerned with randomized algorithms that have been developed during the last decade to solve large-scale linear algebra problems from, for example, scientific computing and statistica
MSE-671: Computation, Modeling and VisualizationThe student has been exposed to the use of modelling, coding, and visualization as a means to understand a research problem more deeply.
The student will have experience in symbolic and numerical of M