Linear programming (LP), also known as linear optimisation, the term “linear programming” consists of two words as linear and programming.
The word “linear” defines the relationship between multiple variables with degree one. The word “programming” defines the process of selecting the best solution from various alternatives.
So, it is a method of finding the best outcome (such as maximum profit or minimum cost) in a mathematical model.
Targeted skills :
The Linear Programming course aims to:
- In terms of knowledge, to teach you express objective function and resource constraints in LP model in terms of decision variables and parameters.
- In terms of know-how:
- To train yourself to understand solution methods, how to use them, and compare different situations to choose the most appropriate method to reach the solution.
- Direct you towards to find the best way to solve the problem by using the primal or the dual problem
La compilation est l'étape qui précède l’exécution d'un programme pour avoir les résultats attendus, c'est un programme qui lit un programme de haut niveau (code source) et le traduit en un programme bas niveau (code cible).
Compétences ciblées :
- Connaitre les différentes phases du compilateur ;
- Comprendre l'objectif de l'analyseur lexicale et comment réaliser un analyseur lexicale ;
- Comprendre les méthodes d'analyse syntaxique ;
- Comprendre la phase sémantique ;
- Comment générer et optimiser le code intermédiaire pour construire le code cible.
A course of this module typically offered in various academic programs such as mathematics, engineering, economics, data science, and other scientific disciplines. This module provides students with a foundational understanding of two key areas: probability theory and statistical methods.
Targeted skills:
- Understanding Probability Concepts.
- Working with Random Variables.
- Statistical Data Analysis.
- Estimation and Hypothesis Testing.