COMP6370: Neural Networks and Deep Learning

This course offers a comprehensive exploration of neural networks and deep learning techniques, covering both foundational principles and advanced methodologies.  Students will be introduced to the basics of artificial neural networks, including feedforward networks, backpropagation, activation functions, and gradient descent optimization. Subsequently, they will delve into advanced topics such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and deep learning architectures like autoencoders and generative adversarial networks (GANs). The course will also cover practical aspects such as data preprocessing, model evaluation, and deployment considerations.