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. or ISTM 315; BUSN 203 or equivalent; admission to upper division in Mays Business School 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. or ISTM 315; BUSN 203 or equivalent; admission to upper division in Mays Business School Credits 3. 3 Lecture Hours.
