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
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.
BIO-212: Biological chemistry IBiochemistry 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
PHYS-307: Physics of materialsThis course discusses materials physics associated with the mechanical and structural properties of solids, primarily focusing on the physics of dislocation defect dynamics and linking diffusion kinet
EE-566: Adaptation and learningIn this course, students learn to design and master algorithms and core concepts related to inference and learning from data and the foundations of adaptation and learning theories with applications.
CH-453: Molecular quantum dynamicsThe course covers several exact, approximate, and numerical methods to solve the time-dependent molecular Schrödinger equation, and applications including calculations of molecular electronic spectra.
ME-351: Thermodynamics and energetics IIThis course will discuss advanced topics in thermodynamics with a focus on studying gas
phases, mixtures, phase transformations and combustion. The application of these principles
to various practical
ME-390: Foundations of artificial intelligenceThis course provides the students with 1) a set of theoretical concepts to understand the machine learning approach; and 2) a subset of the tools to use this approach for problems arising in mechanica
MATH-486: Statistical mechanics and Gibbs measuresThis course provides a rigorous introduction to the ideas, methods and results of classical statistical mechanics, with an emphasis on presenting the central tools for the probabilistic description of