Applied Mathematics

Explore the programs and courses offered by Applied Mathematics

Browse Programs Admission Information

Program Overview

By the completion of the Applied Mathematics Program, students will be able to:

  • Acquire the fundamental elements of algebra, including vector spaces, multilinear algebra, and linear and bilinear forms on finite-dimensional vector spaces,
  • Study the pointwise and uniform convergence of sequences and series of functions of a real variable, power series, and Fourier series,
  • Calculate generalized integrals and study functions defined by an integral,
  • Provide students with essential topology foundations necessary for any mathematical training,
  • Present several numerical resolution methods for various problems, such as integral computation, function approximation, and solving systems of linear equations,
  • Acquire the foundations of set theory and mathematical reasoning,
  • Introduce students to fundamental programming concepts,
  • Study different aspects of multivariable function analysis (real functions), including continuity, differentiability, and multiple integral computation,
  • Introduce the concept of differentiable functions of a complex variable, their properties, and some applications,
  • Familiarize students with probability concepts and techniques,
  • Acquire basic notions of affine and Euclidean geometry,
  • Understand the evolution of mathematical thought through different civilizations,
  • Demonstrate the importance of mathematics by providing examples of its applications in solving problems encountered in physics, astronomy, medicine, etc.,
  • Detail key concepts and methods in probability theory (event probability, distributions and moments of random variables, conditioning and regressions, transformations of random variables, Gaussian distributions),
  • Provide students with fundamental concepts and theorems in statistics,
  • Learn to analyze statistical data presented in tabular form,
  • Model phenomena that depend on time,
  • Present the main classes of time-dependent stochastic phenomena relevant to operational research, statistics, and stochastic calculus,
  • Calculate the optimum of a function with n variables subject to equality or linear inequality constraints,
  • Introduce simulation as a modeling method for studying systems whose analytical or direct study is complex or sometimes impossible,
  • Acquire knowledge related to the Bayesian approach in statistics as a complement to inferential statistics,
  • Learn to write and manipulate LaTeX.


Teaching Language : English

Curriculum Highlights

Core Courses

The Bachelor's degree is structured into six semesters over three years, including a Common Core year in Mathematics and Computer Science (see the Common Core program).


The third semester consists of three teaching units. The first is the fundamental unit, which includes:

- Analysis 3

- Algebra 3

- Introduction to Topology


The methodology unit includes:

- Numerical Analysis 1

- Mathematical Logic

- Programming Tools for Mathematics 2


The discovery unit consists of the subject: History of Mathematics.


The fourth semester also has three teaching units. The fundamental unit includes:

- Analysis 4

- Algebra 4

- Complex Analysis


The methodology unit includes:

- Numerical Analysis 2

- Probability

- Geometry


The discovery unit consists of the subject: Applications of Mathematics to Other Sciences.


The fifth semester follows a similar structure. The fundamental unit includes:

- Advanced Probability

- Parametric Statistics

- Matrix Numerical Analysis


The methodology unit includes:

- Information Systems and Databases

- Exploratory Data Analysis


The transversal unit consists of the subject: Scientific English.


The final semester consists of three teaching units. The fundamental unit includes:

- Subject X

- Stochastic Processes

- Subject Y

- Simulation and Software Practice


The methodology unit includes:

- Subject Z

- Mini Project


The transversal unit includes: Introduction to LaTeX.


**Subject X must be chosen from:**

- Graph Theory

- Time Series


**Subject Y must be chosen from:**

- Linear Programming

- Advanced Algebra and Arithmetic

- Linear and Nonlinear Regression


**Subject Z must be chosen from:**

- Mathematical Programming

- Cryptography and Cryptanalysis

- Nonparametric Statistics


At our institution, based on available academic supervision, the selected options are:

- Time Series

- Linear Programming

- Nonparametric Statistics.

Advanced Topics

Advanced topics include partial differential equations and their numerical solutions, functional analysis, stochastic modeling, and advanced optimization. The program also covers machine learning and artificial intelligence methods applied to mathematics, numerical simulations in engineering and finance, as well as big data analysis for decision-making. These skills enable graduates to pursue careers in fields such as finance, computing, engineering, scientific research, and data analysis.

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Admissions Information

Access to higher education and training is open to holders of a baccalaureate or an equivalent internationally recognized qualification.

Since the 2014/2015 academic year, the Ministry of Higher Education has implemented a new registration procedure, whereby pre-registration, orientation, and appeals for new baccalaureate holders are conducted exclusively online.

To complete these procedures, two official websites are available:

http://www.orientation.esi.dz

http://www.mesrs.esi.dz

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