Advanced Deep Learning

The course Advanced Deep Learning aims at providing students with a good understanding of advanced architectures of deep neural networks and algorithms, along with deriving practical AI solutions in various domains such as economics, fintech, computer vision, natural language processing. The course demonstrates mathematical concepts and hands-on skills required for the algorithms that are typically used in practice. The students will be able to apply concepts and skills to analyze complex data across different domains, then build learning systems and comprehend their performance. The course covers diverse topics including Transfer Learning, Generative Adversarial Network (GAN), Reinforcement Learning (RL), Attention and Transformer Networks, Graph Neural Network (GNN). On the other hand, advanced applications of deep learning will also be addressed, such as natural language processing, robotics, autonomous driving systems, time-series applications, etc.