ST: Introduction to Deep Learning

12 units · Graduate

Intermittent: 12 units This course introduces the deep learning methodology. Students will learn about the basics of deep neural networks, and their applications to different tasks in engineering. Students will be able to apply Deep Learning to a variety of artificial intelligence tasks pertinent to different engineering problems. Neural Networks and Convolutional Neural Networks (CNN) and different variations of it will be taught. The fundamental knowledge and mathematics behind backpropagation and automatic differentiation will be discussed. Deep learning libraries such as Pytorch will be taught, and students will learn to use these libraries for developing deep learning models.