Catégorie

Astronomie

Cours associés (220)

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MATH-305: Introduction to partial differential equations

This is an introductory course on Elliptic Partial Differential Equations. The course will cover the theory of both classical and generalized (weak) solutions of elliptic PDEs.

COM-417: Advanced probability and applications

In this course, various aspects of probability theory are considered. The first part is devoted to the main theorems in the field (law of large numbers, central limit theorem, concentration inequaliti

COM-500: Statistical signal and data processing through applications

Building up on the basic concepts of sampling, filtering and Fourier transforms, we address stochastic modeling, spectral analysis, estimation and prediction, classification, and adaptive filtering, w

CS-526: Learning theory

Machine learning and data analysis are becoming increasingly central in many sciences and applications. This course concentrates on the theoretical underpinnings of machine learning.

MSE-637(b): Transmission electron microscopy and diffraction (b)

This intensive course is intended for researchers who envisage using transmission electron microscopy to study materials samples or to help them interpret TEM data in publications. It presents basics

MATH-101(g): Analysis I

Étudier les concepts fondamentaux d'analyse et le calcul différentiel et intégral des fonctions réelles d'une variable.

CH-410: Physical and chemical analyses of materials

The course relates on the use of electromagnetic (X-Ray) and corpuscular (electrons) radiations for physical and chemical analysis of solid materials.

ChE-201: Introduction to chemical engineering

Introduction to Chemical Engineering is an introductory course that provides a basic overview of the chemical engineering field. It addresses the formulation and solution of material and energy balanc

MATH-106(f): Analysis II

Étudier les concepts fondamentaux d'analyse et le calcul différentiel et intégral des fonctions réelles de plusieurs variables.

BIO-341: Dynamical systems in biology

Life is non-linear. This course introduces dynamical systems as a technique for modelling simple biological processes. The emphasis is on the qualitative and numerical analysis of non-linear dynamical