BIO-465: Biological modeling of neural networksIn this course we study mathematical models of neurons and neuronal networks in the context of biology and establish links to models of cognition. The focus is on brain dynamics approximated by determ
MGT-492: Data science and machine learning IThis class provides a hands-on introduction to data science and machine learning topics, exploring areas such as data acquisition and cleaning, regression, classification, clustering, neural networks,
MATH-455: Combinatorial statisticsThe class will cover statistical models and statistical learning problems involving discrete structures. It starts with an overview of basic random graphs and discrete probability results. It then cov
BIOENG-450: In silico neuroscience"In silico Neuroscience" introduces students to a synthesis of modern neuroscience and state-of-the-art data management, modelling and computing technologies.
MSE-610: Non-destructive evaluation methodsBasic knowledge of the classical non-destructive testing methods as they are used today in industrial applications and the advanced (mostly imaging) technologies used for the analysis of materials and
CS-422: Database systemsThis course is intended for students who want to understand modern large-scale data analysis systems and database systems. It covers a wide range of topics and technologies, and will prepare students
