Crédit : 4 ECTS
Langue du cours : anglais

Volume horaire

  • Volume horaire global (hors stage) : 36 h

Learning Outcomes

On completion of this module, students will be able to:
  1. work confidently with derivatives of multivariable functions
  2. understand basic geometric concepts in IR2 and IR3
  3. optimize a function of 2 variables
Course Objectives

This module aims to provide analytical skills:
  • to be able to differentiate any functions of 1 or 2 variables,
  • to have basic knowledge of topology and apply it to IR2,
  • to know how to find a critical point and determine its nature for a one variable function and a 2 variable function,
  • to know the formulas of Taylor Approximation (1rst order and 2nd Order) and their application (linear approximation and convexity),
  • to know how to find a critical point and determine its nature for a 2 variable function subject to a one-dimension constraint, using substitution
  • to know which hypothesis have to be fulfilled before using an optimization method,
  • to be able to filter and decode information before translating a business world situation into a mathematical model,
  • to be able t translate a business world problem into a mathematical model,
  • to keep a critical eye on model or software outcomes from your work or the work of others

This course provides to techniques of optimization for single-variable and double variable functions. After a deep understanding of the meaning of differentiation and its graphical interpretation, we will address the techniques of optimizations. Mathematical proofs are minimized except when relevant to the understanding of the concepts. Designed as such, it provides the prerequisites for multivariable’s optimization and the Lagrange method.

Grading Criteria
Midterm 1 25%
Midterm 2 25%
Final Exam 50%

Enseignant responsable


Enseignant responsable


Année universitaire 2019 - 2020 - Fiche modifiée le : 15-07-2019 (18H17) - Sous réserve de modification.