The Applied Elements of Artificial Intelligence course introduces the fundamental concepts and practical applications of modern AI. Students learn the basics of Machine Learning, Deep Learning, supervised and unsupervised learning, and neural networks. The course also covers the mathematical foundations of AI and the use of Python libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, and PyTorch. Through practical exercises and a mini-project, students develop AI models for classification and clustering tasks. They also learn how to evaluate model performance and apply AI techniques to solve real-world engineering problems while considering ethical and responsible AI practices.
- Enseignant: Inas BOUZATEUR