The course focuses on the challenge of integrating AI into Embedded Systems in which students will learn how to apply fuzzy logic and neural networks to handle with real time data in embedded systems. It covers 2 major parts:

Part 1: describes AI field, history and applications as well as its relationship with embedded systems

Part 2: details fuzzy logic and inferences, neural networks (from biology to mathematical representation of MLP), then their application in embedded systems

Essalem,

Welcome to this course ...

Ce module explore les concepts avancés du Machine Learning (ML), en mettant l'accent sur des méthodes modernes, des approches algorithmiques avancées et leur application à des problèmes complexes. Les étudiants approfondiront des techniques telles que l'apprentissage supervisé, non supervisé, semi-supervisé, ainsi que l'apprentissage par renforcement. Une attention particulière sera accordée à des sujets de pointe, notamment les réseaux de neurones profonds (Deep Learning), les architectures avancées comme les réseaux convolutifs (CNN), les réseaux récurrents (RNN), et les modèles génératifs (GAN).

Le cours combine des bases théoriques solides avec des applications pratiques, favorisant la maîtrise des outils et frameworks populaires (TensorFlow, PyTorch). À la fin de ce module, les étudiants seront capables de concevoir, entraîner et évaluer des modèles ML complexes, et de les appliquer dans des domaines variés comme la vision par ordinateur, le traitement du langage naturel, ou encore les systèmes de recommandation.

Interaction and Implication The concepts of "software engineering" (or software engineering) and artificial intelligence (AI) are two interconnected fields that play a vital role in the development of modern software systems. The integration of artificial intelligence into software engineering offers significant opportunities to improve efficiency, quality, and innovation in application development. By taking advantage of these technologies, development teams can respond more quickly to user needs and create more robust and adaptive solutions.

 The goal of this module is to provide an in-depth understanding of the evolution of software development, exploring its historical context, key phases, and the impact of technological advancements and user needs. By the end of the lecture, participants should be able to:

1.     Identify the major milestones in the history of software development.
2. Describe the different phases involved in the software development lifecycle.
3.   Understand the influence of emerging technologies on software development methodologies.
4.   Recognize current trends and future directions in software development practices.