Academic Year 2025-2026
Complete syllabus outlining all topics covered in this course, and learning objectives.
View Course PlanFoundational principles of AI: knowledge representation, reasoning systems, and intelligent agents.
View Course (French)General overview of course objectives, practical sessions, and evaluation.
View Course (French)Introduction to biological neurons and the core algorithms of the Perceptron, multilayer Perceptron, and artificial neural networks.
View Course (French)Introduction to deep learning concepts and neural architectures, including Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs).
View Course (French)Introduction to logic-based systems, symbolic reasoning, and applications in natural language understanding.
View Course (French)The evolution of AI methodologies, major milestones, classification algorithms, and their evaluation.
View Course (French)Interactive visualization of a single-layer perceptron, the foundational model of neural networks.
Explore PerceptronVisualization of how multiple perceptron layers collaborate to solve non-linear classification tasks.
Explore MLPArchitecture and data flow through deep neural networks with multiple hidden layers.
Explore DNNComprehensive repository containing Jupyter notebooks, code samples, and project templates with bilingual documentation.
Access on GitHub