CS-550: Formal verificationWe introduce formal verification as an approach for developing highly reliable systems. Formal verification finds proofs that computer systems work under all relevant scenarios. We will learn how to use formal verification tools and explain the theory and ...
PHYS-314: Quantum physics IIThe aim of this course is to familiarize the student with the concepts, methods and consequences of quantum physics. ...
ENV-300: Pollutants analysis in the environmentÉvaluation de la qualité d'une rivière en utilisant des méthodes d'observation ainsi que des méthodes physico-chimiques et biologiques. Collecte d'échantillons sur le terrain et analyses de laboratoire.
Détermination pratique et utilisation des constantes ...
ENV-471: Environmental economicsIntroduction to economic analysis applied to environmental issues: all the necessary basic concepts, including cost-benefit analysis, for environmental policy making and its instruments (examples: climate, waste, mobility). Introduction to financial calcul ...
ENV-504: Groundwater and soil remediationThis course covers the essential knowledge of contaminant partitioning and techniques to monitor chemical species, physical extent of contamination and biological processes. In the second part, remediation approaches are tackled. This course represents the ...
MSE-351: Surface analysisThe course treats the main surface analysis methods for the characterization of surfaces, interfaces and thin films. It discusses how these methods can be applied to gain specific knowledge about structural, chemical and functional properties of surfaces a ...
CIVIL-321: Numerical modelling of solids and structuresLa modélisation numérique des solides est abordée à travers la méthode des éléments finis. Les aspects purement analytiques sont d'abord présentés, puis les moyens d'interpolation, d'intégration et de résolution de la mécanique sont étudiés. ...
CS-401: Applied data analysisThis course teaches the basic techniques, methodologies, and practical skills required to draw meaningful insights from a variety of data, with the help of the most acclaimed software tools in the data science world (pandas, scikit-learn, Spark, etc.) ...
PHYS-467: Machine learning for physicistsMachine learning and data analysis are becoming increasingly central in sciences including physics. In this course, fundamental principles and methods of machine learning will be introduced and practised. ...
MGT-426: Logistics and demand analysisLa logistique, fonction transversale par excellence, intègre toutes les dimensions des processus industriels à ajout de valeur, de l'approvisionnement à la distribution aux clients et au-delà en intégrant le développement durable. Un focus particulier sera ...
ENG-410: Energy supply, economics and transitionThis course examines energy systems from various angles: available resources, how they can be combined or substituted, their private and social costs, whether they can meet the energy demand, and how the transition to a renewable energy system can be foste ...
CIVIL-438: Risk analysis and managementLe cours vise à former les étudiants aux méthodes et outils permettant d'appréhender de manière fondée et scientifique la question de l'analyse et de la gestion des risques technologiques et naturels, avec une attention portée au domaine du Génie civil. ...
CS-101: Advanced information, computation, communication IDiscrete mathematics is a discipline with applications to almost all areas of study. It provides a set of indispensable tools to computer science in particular. This course reviews (familiar) topics as diverse as mathematical reasoning, combinatorics, disc ...
PHYS-207(a): General physics : quantaCe cours est une introduction à la mécanique quantique. En partant de son développement historique, le cours traite les notions de complémentarité quantique et le principe d'incertitude, le processus de mesure, l'équation de Schrödinger, ainsi que des élém ...
EE-619: Advanced topics in network neuroscienceThe main goal of this course is to give the student a solid introduction into approaches, methods, and tools for brain network analysis. The student will learn about principles of network science and how to implement and develop methods and tools for graph ...
