Applied Predictive Analytics

Catalog description

Credits 3. 3 Lecture Hours. Development and application of predictive analytics to business problems using state-of-the-art software tools; implementation, validation and testing of models that employ machine learning methods and artificial intelligence; hands-on, practical approach to project-based predictive analytics using real-world data sets. Prerequisite: ISTM 313 or ISTM 315 ; BUSN 203 or equivalent; admission to upper division in Mays Business School.