Introduction

Abdelhafid Boussouf University of Mila

Faculty of Mathematics an Computer Science

  • Field: Mathematics and Computer Science.
  • Teaching unit: Methodological;
  • Subject: Programming tools II.
  • Level: 2nd year mathematics and applied mathematics 
  • Semester: 3, Academic year: 2025/2026
  • Credit: 3, Coefficient: 1
  • Weekly Hourly Volume: 3h
  1.  Lecture (1 hour 30 minutes)-
  2.  Practical work (1 hour 30 minutes)
  • Language of instruction: English
  • Teacher responsible for the subject: Dr. Messaoud BERKAL
  • Emails: berkalmessaoud@gmail.com, or m.berkal@centre-univ-mila.dz.
  • Goals: This course is intended for second-year undergraduate students and is part of the methodological teaching unit. Its primary objective is to introduce students to the fundamental concepts of the MATLAB and SCILAB programming languages, enabling them to rapidly develop autonomy in using these software tools. Through this course, students will be able to:

  1. Understand the basic structure and syntax of MATLAB and SCILAB programs;
  2. Perform numerical computations and data analysis efficiently;
  3. Create and manipulate vectors, matrices, and arrays;
  4. Develop scripts and functions for solving mathematical and engineering problems;
  5. Visualize data using appropriate graphical tools;
The course is divided into seven chapters:

  1. Chapter 1: General and getting started
  2. Chapter 2: Vectors
  3. Chapter 3: Matrices
  4. Chapter 4: Programming in Matlab Chapter 
  5. Chapter 5: Polynomials and functions in MATLAB
  6. Chapter 6: Graphical representation in Matlab
  • Bibliography:

[1] H. Moore, MATLAB for Engineers. A practical approach for learning MATLAB, focused on

applications relevant to engineering and mathematics.

[2] S. Attaway, MATLAB: A Practical Introduction to Programming and Problem Solving. A

beginner-friendly book introducing MATLAB programming and problem-solving techniques.

[3] V. Cheng, MATLAB for Data Analysis. Focuses on MATLAB for data analysis, visualization,

and numerical computing for mathematicians.

[4] J. Sizemore and J. P. Mueller, MATLAB for Dummies. An accessible guide to learning MATLAB,

covering basics to advanced topics.

[5] A. Gilat, MATLAB: An Introduction with Applications. A comprehensive introduction with

applications in engineering, science, mathematics, and economics.

[6] R. S. S. P. Vishnu, MATLAB for Engineers and Scientists. A practical guide for engineers and

scientists using MATLAB-based solutions for real-world problems.

[7] J. Boyd, MATLAB for Machine Learning. A specialized book applying machine learning

algorithms and concepts using MATLAB.

  • Evaluation mode

      Continuous evaluation: 40%,   Final exam: 60%.



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