MATH-493: Applied biostatisticsThis course covers topics in applied biostatistics, with an emphasis on practical aspects of data analysis using R statistical software. Topics include types of studies and their design and analysis,
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
MATH-432: Probability theoryThe course is based on Durrett's text book
Probability: Theory and Examples.
It takes the measure theory approach to probability theory, wherein expectations are simply abstract integrals.
MATH-442: Statistical theory-This course gives a mostly rigourous treatment of some statistical methods outside the context of standard likelihood theory.
FIN-415: Probability and stochastic calculusThis course gives an introduction to probability theory and stochastic calculus in discrete and continuous time. The fundamental notions and techniques introduced in this course have many applicatio
MGT-581: Introduction to econometricsThe course provides an introduction to econometrics for economics and financial applications. The objective is to learn how to make valid (i.e., causal) inference from economic and social data.
MICRO-573: Deep learning for optical imagingThis course will focus on the practical implementation of artificial neural networks (ANN) using the open-source TensorFlow machine learning library developed by Google for Python.
EE-554: Automatic speech processingThe goal of this course is to provide the students with the main formalisms, models and algorithms required for the implementation of advanced speech processing applications (involving, among others,
