This course covers advanced topics in statistical and deep learning and provides statistical and computational fundamentals of artificial neural networks for complex high-dimensional data. Course topics include multilayer deep neural networks, convolutional neural networks, recurrent neural networks, generative adversarial networks, graphical neural networks, autoencoders, and restricted Boltzmann machines. Students will be introduced to contemporary deep learning platforms such as TensorFlow, PyTorch, and H2O with applications of computer vision and natural language processing. Prerequisite: DAAN 704. (F;S;SS)