This course focuses on deep learning, one of the most important areas of artificial intelligence that relies on multi-layer artificial neural networks. The course will cover the fundamentals of neural networks, design of multi-layer networks (MLPs), convolutional neural networks (CNNs) for computer vision, and recurrent neural networks (RNNs) for processing sequential data. 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