This course introduces fundamental components of deep learning system, including Linear Classifiers, Stochastic Gradient Descent, Fully Connected Networks, Convolutional Networks, and Recurrent Networks. Additionally, it introduces applications of deep learning, emphasizing the core concepts behind these applications, such as Object Detection, Image Segmentation, Video Classification, Generative Models, and Reinforcement Learning.