Applied Machine Learning: Team Projects credit:

4 Hours

A comprehensive exploration of the applied machine learning workflow from inspiration to delivery of a machine learning solution broadly defined (i.e., from analytic finding to embedded machine learning application). This course is firmly grounded in a "learning-by-doing" teaching philosophy with pedagogical priority clearly placed on the application of machine learning to real-world data and problems. Ongoing and intense practical experiences in team-based project management and work are another cornerstone of this course. This course includes student-led reviews of existing data sources and machine learning technologies along with several team-based fact-finding and proof-of-concept implementation projects. This course is designed for students wishing to engage seriously in the practical world of machine learning implementation. Prerequisite: Students should have demonstrated ability, and must have taken one of the following courses, IS 577 (formerly IS 590 DT), IS 517 (formerly IS 590 MD), CS 412 , CS 446 or a course demonstrably equivalent.