This course focuses on deep learning, which is one of the most important areas of artificial intelligence that relies on multi-layered artificial neural networks. The course will cover the fundamentals of neural networks, the design of multilayer networks (MLPs), convolutional neural networks (CNNs) for computer vision, and redundant neural networks (RNNs) for serial data processing. In addition, students will learn model optimization techniques such as optimization algorithms, transfer learning, and generative models. Students will be trained to use machine learning libraries such as TensorFlow and PyTorch to design and implement deep learning models