mathematics - licence

Explore the programs and courses offered by mathematics - licence

Browse Programs Admission Information

Program Overview

  • Strong foundation in both pure and applied mathematics
  • Emphasis on algorithmic thinking, programming, and scientific computing
  • Introduction to physics, computer architecture, and data structures
  • Development of skills in research, scientific communication, and languages
  • Opportunity to specialize in advanced topics in the final semester
  • Balanced education combining theory and practice (lectures, tutorials, labs)


Teaching Language : English

Curriculum Highlights

Core Courses

Semester 1:

Analysis 1 (real numbers, sequences, derivatives)

Algebra 1 (logic, sets, basic structures)

Algorithms and Data Structures 1

Machine Structure 1 (number systems, Boolean algebra)

Scientific Terminology and Written Expression

Foreign Language (Scientific English or French)

Physics 1 or Electronics (elective)

Semester 2:

Analysis 2 (integration, basic differential equations)

Algebra 2 (vector spaces, linear mappings)

Algorithms and Data Structures 2

Machine Structure 2 (logic circuits, automata)

Probability and Descriptive Statistics

Information and Communication Technologies (ICT)

Programming Tools (e.g., MATLAB, Scilab)

Physics 2 (electricity and magnetism)

Semester 3:

Analysis 3 (series, Fourier series, improper integrals)

Algebra 3 (eigenvalues, matrix reduction, Jordan form)

Introduction to Topology

Numerical Analysis 1

Mathematical Logic

Programming 2

History of Mathematics

Semester 4:

Analysis 4 (advanced analysis, continuity, fundamental theorems)

Algebra 4

Complex Analysis

Numerical Analysis 2

Probability

Geometry

Applications of Mathematics in Other Sciences


Advanced Topics

Semester 5:

Measure and Integration

Normed Vector Spaces

Differential Equations and Mathematical Physics

Unconstrained Optimization

Introduction to Mathematics Didactics

Semester 6:

Choose two subjects from the following:

Group Theory

Linear Operator Theory

Inferential Statistics

Partial Differential Equations (PDEs)

Constrained Optimization

Stochastic Processes

Linear Programming

Mathematical Modeling of Living Systems

Numerical Methods for ODEs and PDEs

Integral Transforms in LpL^p Spaces

Differential Geometry

Ethics and Professional Conduct in Teaching and Research


Admissions Information

Required Diploma: Required diploma: Scientific Baccalaureate (Experimental Sciences, Mathematics, or Technical Mathematics)

Admission Method: National orientation through the online pre-registration platform

Entrance Exam: None


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