Advanced Topics in Deep Learning for Computer Vision

The course covers the theory and practice of deep learning with a focus on applications in computer vision. Students will learn the foundational mathematics behind deep learning and explore topics such as multi-layer perceptrons (MLPs), back-propagation and automatic differentiation, convolutional neural networks (CNNs), recurrent neural networks (RNNs), and Transformers. These techniques play a crucial role in modern AI systems, including image and video understanding, natural language processing, generative AI, and robotics. The various practical assessments will enhance student's understanding and intuition of deep learning and its application in computer vision.