This course introduces fundamental principles of deep learning and computer vision. It focuses chiefly on deep neural network (DNN) and its models for solving computer vision problems. Topics include data manipulation, regularization, optimization, convolutional neural network (CNN), image classification, object detection, and basic generative adversarial network (GAN). We will develop the intuitions in class, and then implement models in projects.