Available courses

Analyse Conception Orientée Objet

Génie Logiciel

Apprendre à appliquer une méthodologie d'analyse et de conception pour le développement des logiciels. En particulier, apprendre la modélisation object avec le langage universel UML.

English1

This course provides a comprehensive set of topics and lessons for students between A2 and B1 levels, with a focus on communication in daily life. Each lesson includes structured activities that integrate speaking, listening, and grammar practice to help students improve their English fluency in a variety of everyday situations

English2

This course builds on the first semester’s English Communication module and aims to further develop students’ ability to use English confidently and naturally in real-life situations. Through topics such as travel, shopping, technology, communication, and social interactions, students expand their vocabulary, improve grammatical accuracy, and strengthen fluency in spoken English. The course emphasizes practical communication skills, including making polite requests, expressing opinions, describing experiences, and participating in extended conversations, while integrating listening and speaking activities to enhance coherence, interaction, and overall communicative competence.

Algorithmic and Data Structures 1

Algorithmic and Data Structures 2

Digital Economy and Strategic Vigilance

Startup and Professional Development

Operating System: Synchronisation and Communication

Course Description 

The Operating Systems: Synchronization and Communication course delves into the fundamental concepts of parallelism and concurrency within operating systems. It examines essential mechanisms for process synchronization and inter-process communication (IPC), along with the primary challenges of concurrent execution. Key topics include mutual exclusion, process synchronization, communication models, monitors, and deadlock management. Practical aspects emphasize hands-on UNIX implementations using tools such as processes, signals, semaphores, shared memory, message queues, and pipes.

Target Audience: 3rd-year Artificial Intelligence Engineering students 

Génie Logiciel

Innovation and Entrepreneurship

This course introduces the key principles of innovation and entrepreneurship, focusing on how ideas are generated, developed, and transformed into viable business opportunities. It covers creativity, opportunity recognition, business model design, and startup development. Students learn to evaluate ideas, understand market needs, and apply tools such as the Business Model Canvas. The course also highlights real-world challenges in launching and managing new ventures, fostering creativity, critical thinking, and an entrepreneurial mindset.

Operating Systems Security

Operating System Security refers to the set of:

  • Architectural mechanisms

  • Enforcement policies

  • Verification chains

that collectively ensure:

  • Controlled access to system resources

  • Strong isolation between execution contexts

  • Integrity of the kernel and trusted components

  • Resistance to privilege escalation and persistence attacks

Deep Learning

Course Description : This course provides a comprehensive introduction to deep learning, covering fundamental concepts, architectures, and advanced techniques. Students will explore the theoretical foundations and practical applications of neural networks, including feedforward networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative models. The course emphasizes hands-on experience through practical work sessions where students implement deep learning models using modern frameworks such as TensorFlow and PyTorch.

Target Students: 4th Ing. AI

Techniques d'optimisation pour les réseaux

\(Headings CS\)'; color: #004c2d; mso-themecolor: accent3; mso-themeshade: 191; text-transform: uppercase; mso-fareast-language: JA;">Présentation générale du cours

Ce cours de « Techniques d’optimisation pour les réseaux » explore les méthodes mathématiques et algorithmiques pour modéliser et résoudre les problèmes d’optimisation dans les réseaux informatiques. Ce cours est structuré en cinq chapitres (unités d'apprentissage), chacun étant conçu pour présenter les principes essentiels des différentes techniques d’optimisation et leur application dans les réseaux informatiques. Tout au long des chapitres, les étudiants exploreront les concepts clés à travers des séquences pédagogiques étape par étape, garantissant ainsi une compréhension progressive et approfondie du sujet.

\(Headings CS\)'; color: #004c2d; mso-themecolor: accent3; mso-themeshade: 191; text-transform: uppercase; mso-fareast-language: JA;">OBJECTIFS PÉDAGOGIQUES 

Ce cours vise à :

  •         Connaître les enjeux, critères et paramètres d’optimisation dans les réseaux.
  •         Comprendre et maîtriser les outils mathématiques pour modéliser et optimiser les réseaux.
  •         Appliquer des algorithmes exacts et approchés à des problèmes réels comme le routage ou la topologie.

\(Headings CS\)'; color: #004c2d; mso-themecolor: accent3; mso-themeshade: 191; text-transform: uppercase; mso-ansi-language: EN-US; mso-fareast-language: JA;">Connaissances Préalables Recommandées

Pour suivre ce cours avec succès :

  •         Bases en recherche opérationnelle (théorie des graphes, …).
  •         Notions en réseaux informatiques (modèles OSI/TCP-IP, …).
  •         Fondamentaux en algorithmique.

Soft Skills: Amélioration des Compétences Comportementales

This course aims to develop the behavioral and interpersonal competencies that are essential for engineering students in both academic and professional environments. Through a combination of short theoretical inputs, practical exercises, and real-world simulations, students will learn how to communicate effectively, collaborate in teams, solve problems critically, present technical ideas persuasively, and demonstrate soft skills in recruitment and career contexts. At the end of the course, students are expected to understand the relevance of soft skills in engineering careers and to apply them confidently in real situations.

modeling and performance evaluation of computer networking

This course introduces students to the principles of modeling computer networking behaviors to evaluate their performance. It concentrates on the queuing theory and probabilistic models, especially Markov chains, to be exploited in the modeling process. At the end of this course, students will be able to manipulate probabilistic models and Markov chains for evaluating computer network performances.

Méthodologie de recherche

L’objectif de ce cours est :

- de donner un aperçu sur les méthodes de la Recherche Scientifique,

- d'initier les étudiants aux normes de rédaction de mémoire et

- comment préparer et soutenir son travail de Master.

Il comporte deux parties :

Partie 1 : Méthodes de la Recherche Scientifique 

Partie 2 : Rédaction de Mémoire & Soutenance Orale

Initiation à la recherche

Permettre aux étudiants de s’initier aux principales méthodes de recherche, de mener correctement un projet de recherche, et de savoir communiquer les résultats de la recherche.

Design and deployment of network infrastructure

Cloud and Virtualization

students are expected to gain comprehensive knowledge and practical skills in several key areas. Firstly, they will learn the fundamentals of cloud computing, service models and deployment models. The course will delve into virtualization technologies, which are the backbone of cloud services, explaining how they enable the efficient use and allocation of computing resources. A significant focus will be on OpenStack, an open-source platform for cloud computing.

All courses