Classical Mechanics

Module Description

Classical Mechanics introduces the fundamental principles governing the motion and interactions of physical bodies. The module covers kinematics, Newton’s laws of motion, work, energy, momentum, and conservation laws. Through mathematical modelling and problem-solving, students develop the analytical skills and physical understanding required for advanced engineering studies, particularly in robotics, autonomous vehicles, and autonomous systems dynamics.

Probability and Statistics

This course provides students with a solid foundation in probability and statistics, essential tools for data analysis and decision-making in scientific and engineering contexts.

The module is structured in two main parts:

  • Statistics: Students learn how to describe and analyze data through one- and two-variable statistical series. Topics include data representation (tables and graphs), measures of central tendency and dispersion, and the study of relationships between variables using correlation and regression methods.
  • Probability: The course introduces the fundamental concepts of probability theory, including combinatorial analysis, probability spaces, and key theorems. Students also explore conditional probability, independence, and Bayes’ theorem, before studying random variables and their properties. Common discrete and continuous probability distributions such as binomial, Poisson, and normal laws are also covered.

Throughout the course, emphasis is placed on both theoretical understanding and practical applications, preparing students for further studies in data science, engineering, and applied mathematics.

Assessment is based on continuous evaluation (quizzes, assignments) and a final examination.

ALGEBRA 2

This  algebra 2 course focuses on the core concepts of vector spaces, matrices, and linear transformations. Students will explore the essential properties of vector spaces, learn to recognize their underlying structure, and identify subspaces. A significant emphasis is placed on matrices, particularly operations including addition, multiplication, and inversion. Linear transformations, expressed using matrices, will be examined to illustrate their importance across different fields. The course also covers diagonalization, enabling students to simplify matrix computations and analyze properties such as eigenvalues and eigenvectors, along with its practical applications in areas like dynamical systems, powers of matrices, and recurrence relations. The goal of the course is to establish a strong foundation in these key topics, equipping students to apply them effectively in both problem-solving contexts and real-world situations.

Electricity and Magnetism

Course Goal

Physics II: Electricity and Magnetism is a foundational course designed for engineering and applied science students. Its primary goal is to develop a rigorous understanding of electric and magnetic fields and their practical applications in modern technology. The course introduces students to the fundamental laws governing electromagnetic phenomena and emphasizes their use in analyzing and solving real engineering problems.

Electromagnetic principles underlie power generation and transmission, electronics, communication systems, sensors, control technologies, and advanced materials. By the end of the course, students will understand how a unified set of physical laws explains a broad range of electrical and magnetic phenomena and how these laws are applied in engineering systems.

The course integrates conceptual understanding with strong mathematical modeling, preparing students for advanced coursework in electrical engineering, electronics, telecommunications, mechatronics, energy systems, and related applied fields.

Introduction to Programming

This subject has the following objectives :

- Have an overview of the architecture of a computer.
- Master the practice of the four operations in base 2, 8 and 16.
- Develop algorithmic reasoning to help solve different problems
- Use the tools of the C language to implement algorithmic solutions.
- Master the basic notions of programming such as conditional and iterative actions.
- Know how to use tables, strings, and structures (records) to store and manipulate various data.