Special Course (Inverse and Ill-Posed Problems) Math690 (EN)
Essential Mathematics for Social Science Math003 (AR)
Calculus I Math101
Calculus II MATH203
Differential Equations Math319
Linear Programming Math453
Analysis in Several Variables Math424
Special Topics in Mathematics Math490
Mathematical Modeling (EN). It introduces the basic concepts and principles of mathematical modeling. This includes modeling discrete change, model fitting and regression, experimental modeling, modeling continuous change, linear and nonlinear optimization modeling. The course contains 4 project assignments
Introduction to Image Processing and its major Research Problems: a fortnight graduate seminar
Calculus I
Mathematics for Information Technology
Scientific Computing for Engineers (FR). This course begins with a description of computer utilities for scientific computation and then covers the following topics: computer arithmetic and error analysis, principles of mathematical modeling, discrete dynamical systems and equations of finite differences, modeling with differential equations (ordinary and partial)
Introduction to Image Processing (FR). Primary intended for engineering students in Networks and Telecommunication, this course introduces the fundamental notions of numerical images, amelioration, debluring, contours detection, morphological operations and compression. It includes an introduction to Matlab Image Processing Toolbox
Mathematical Analysis II. This covers improper integrals, ODE's including systems, functions of several variables, multiple integrals and integrals depending on a parameter
Signal and Systems. Primarily intended for engineering students in preparatory classes, it includes an introduction to Matlab
Introduction to Numerical Optimization. This covers basic methods for unidimensional unconstrained optimization: golden search, quadratic and cubic interpolation, Newton-Raphson, bisection, secant, inexact line searches, and for multidimensional optimization: Newton, Modified Newton, Marquardt, quasi-Newton, conjugate gradient, truncated Newton. It includes laboratories with Matlab
Numerical Analysis (FR). This covers floating point arithmetic, error analysis, solving linear systems, roots for nonlinear equations, interpolation, numerical differentiation and integration. Laboratories are conducted for each chapter on Matlab