AI 447: Deep Learning

This course introduces the fundamental concepts and techniques of Deep Learning, a subfield of artificial intelligence that uses multi-layer neural networks to learn complex patterns from data. Students will learn the principles of deep neural networks, model architectures, training techniques, and optimization methods used in modern AI systems. The course covers key architectures such as Artificial Neural Networks (ANNs), Convolutional Neural Networks (CNNs), and Recurrent Neural Networks (RNNs), along with concepts such as regularization, transfer learning, and model evaluation. Students will gain hands-on experience in designing, training, and applying deep learning models to real-world problems in areas such as computer vision, natural language processing, and predictive analytics.