Session Janvier 2026

This course, "Electrochemical Conversion of Hydrogen" offers a deep dive into the technology at the heart of the transition to a clean and sustainable energy economy. As the world seeks to combat climate change, fuel cells have emerged as a critical solution, converting the chemical energy of hydrogen directly into electricity and heat with high efficiency and zero emissions.

Ce module introduit les notions fondamentales de la mécanique du point matériel. Il permet aux étudiants de comprendre et d’analyser les grandeurs physiques ainsi que les concepts de la cinématique, à travers une approche progressive combinant cours théoriques et exercices pratiques.

Il vise à développer la compréhension des lois du mouvement et à renforcer les capacités d’analyse et de résolution de problèmes en physique.

This course introduces the main concepts and techniques of numerical analysis for solving mathematical problems. It covers polynomial interpolation (Lagrange, Newton, and Hermite methods), least-squares approximation, numerical differentiation, and numerical integration. Emphasis is placed on error analysis, accuracy, and the selection of appropriate numerical methods for scientific and engineering applications

• Teacher:  Ahlem Benzahi

Welcome to Study Skills, a course designed to equip second-year undergraduate EFL students with the essential academic and transferable skills required for success in higher education and lifelong learning. Throughout this course, you will explore five interconnected areas that contribute to effective learning: active learning, reflective learning, critical thinking, decision-making, and problem-solving.

The course is organized into two complementary chapters. The first chapter introduces the concepts of active and reflective learning, emphasizing how meaningful engagement, collaboration, and self-reflection can improve learning experiences and academic performance. The second chapter focuses on critical thinking and problem-solving, enabling you to analyse information objectively, evaluate evidence, make informed decisions, and develop effective solutions to authentic academic and real-life challenges.

To support your learning, the course combines theoretical explanations with interactive activities, case studies, reflective tasks, quizzes, and formative assessments. These learning experiences are intended to help you become a more autonomous learner, strengthen your analytical abilities, and apply higher-order thinking skills in different educational contexts.

By actively participating in this course, you will develop the confidence and competence to learn more effectively, think more critically, and approach challenges with informed judgment and creativity. We encourage you to engage fully with each activity and view this course as an opportunity to strengthen the skills that will benefit you throughout your university studies and your future professional career.

Ce module est destiné aux étudiants de première année des Écoles Normales Supérieures. Il vise principalement à renforcer les acquis antérieurs en mathématiques et à assurer la transition avec les exigences de l’enseignement universitaire, en comblant les lacunes éventuelles.

Sur le plan du contenu, le module s’articule autour de trois axes principaux :

• Le raisonnement et la démonstration mathématique : notions de logique, types de raisonnement et méthodes de preuve (récurrence, contradiction, contre-exemple, etc.).

• Les activités numériques : étude des ensembles de nombres (ℕ, ℤ, ℚ, ℝ), opérations, divisibilité, nombres premiers, division euclidienne et résolution d’équations.

• Les activités géométriques : bases de la géométrie euclidienne, étude des figures (triangles, cercles), vecteurs et équations de la droite et du cercle.

Sur le plan pédagogique, le module repose sur :

• une progression du simple au complexe,

• l’articulation entre théorie et pratique,

• la diversification des exercices (fermés et ouverts),

• l’implication active des étudiants dans la recherche, la discussion et l’analyse.

L’évaluation se fait à travers :

• des questions orales,

• des travaux à domicile,

• des contrôles écrits.

Dans l’ensemble, ce module vise à développer chez l’étudiant une pensée mathématique rigoureuse, en combinant compréhension théorique, pratique et capacité de raisonnement.

The Basic Mathematics course is a core 

learning module designed for first-year

university students in Arabic language.

This course aims to bridge the gap between

secondary school knowledge and university

requirements, with a focus on developing

sound mathematical reasoning skills.

Course Summary

Programming is the process of designing instructions that enable computers to solve problems. This course introduces students to fundamental programming concepts using the C language, focusing on control structures and arrays through practical activities and problem-solving exercises.

Target Audience: First-year computer science teacher (PES)

General Learning Outcomes

At the end of this course, students will be able to:

• Define algorithms, programs, variables, and arrays.
• Explain sequential, conditional, and iterative structures.
• Develop simple C programs.
• Analyze computational problems.
• Evaluate alternative algorithmic solutions.
• Design complete programs to solve practical problem

Course Description:

This course provides an in-depth introduction to the fundamental concepts of knowledge representation and reasoning in Artificial Intelligence. It explores various approaches used to model, structure, and exploit information within intelligent systems, including non-classical logics, probabilistic reasoning, and fuzzy logic.

Special emphasis is placed on understanding how intelligent systems make decisions in complex, uncertain, or incomplete environments. Through practical examples, exercises, and interactive activities, students will learn how to design formal models and select appropriate reasoning techniques depending on the context.

This course serves as a foundational component for the development of intelligent systems and prepares students for advanced applications in artificial intelligence, data science, and decision-support systems.

Target Audience:

This course is intended for 4th-year engineering students in Computer Science, with prior knowledge in logic, discrete mathematics, and basic AI concepts.

Learning Objectives

At the end of this course, students will be able to:
Identify the essential concepts of knowledge representation and reasoning in Artificial
Intelligence, through short conceptual questions and guided examples.
Differentiate classical logic from non-classical logics, by correctly classifying rea-soning
situations from simple Artificial Intelligence scenarios.
Interpret the main formalisms studied in this course, namely modal logic, default log-ic, and
description logics, through symbolic expressions and structured exercises.
Compare the main approaches to uncertain reasoning, particularly Dempster–Shafer Theory
and Bayesian Networks, by identifying their characteristics and fields of application in
guided case studies.
Choose the most suitable reasoning method for a simple Artificial Intelligence problem, by
justifying your choice based on the nature of the represented knowledge.

This course introduces students to the English vowel system, focusing on the Cardinal Vowel System, Monophthongs, Diphthongs, and Triphthongs. Students will develop theoretical knowledge and practical skills in identifying, describing, transcribing, and producing English vowel sounds using the International Phonetic Alphabet (IPA).