Advanced Artificial Intelligence Models and Methods

"Artificial intelligence and computer vision are at the core of numerous applications, ranging from image and video analysis to autonomous robotics and human-computer interaction. Recent advances in deep learning have enabled the development of increasingly accurate and efficient models.

This course introduces advanced methodologies in computer vision and deep learning, with a particular focus on self-supervised learning, generative modeling, and explainable artificial intelligence. Additional topics include the distillation, compression, and optimization of deep neural networks, aimed at improving their efficiency, adaptability, and interpretability.

Basic knowledge of machine learning and deep learning is required, including familiarity with neural networks, supervised learning, and the main architectures used in computer vision.

The course combines theoretical lectures and hands-on activities to provide students with the tools needed to understand, design, and evaluate advanced artificial intelligence models for computer vision applications."