This course aims at exploring issues in the applications of AI to arts and creativity. We will look at principles and algorithms for generation and creation of art design. Students will develop a conceptual understanding of machine learning, and apply practical solutions of algorithms as part of their creative practices. The course will start with the study of deep neural networks. Students will learn to understand the basic principles of neural networks with minimal mathematical requirements. After learning and experimenting with Convolutional Neural Networks (CNN) applications such as image classification and segmentation, the class will move on to introduce Generative Adversarial Networks (GANs). The history of GANs and different derivative structures will be introduced through examples of creative applications. Generative arts in various other multimedia modalities such as text, music, and motion will be briefly introduced as case studies for more inspiration. Finally, students will apply the knowledge learnt to develop art installation prototypes that involve generative models in a group collaborative project.