ESE 5460 Principles of Deep Learning

Short Description

The purpose of this course is to deconstruct the hype by teaching deep learning theories, models, skills, and applications that are useful for applications. Here, we will shed light on the methods behind the magic of Deep Learning. But we don't stop there: We further look into the societal implications of deep learning and how we can design more ethical algorithms.

Portfolio Building Course

No

Pre-Requisites

MCIT Online Students must have completed 4 of their core courses and CIS 5150 or ESE 5420 | MSE-DS Online Students must have completed 5 courses including CIS 5150 or ESE 5420.

Content

Deep networks are at the heart of modern approaches in computer vision, natural language processing and robotics. Design of these networks requires a combination of intuition, theoretical foundation and empirical experience; this course discusses general principles of deep learning that cut across these three. It develops insight into popular empirical practices with a focus on the training of deep networks, builds theoretical skills to develop new ideas in deep learning and to deploy deep networks in real world applications. A fair degree of mathematical and programming proficiency is necessary to complete the coursework.

Course Creators

• Pratik Chaudhari