Undergraduate and Graduate
BAN 302 Predictive Analytics (Undergraduate) This course covers solving problems in the business environment by using predictive analytics techniques. Modeling techniques such as linear regression, logistic regression, classification and regression trees, neural networks, cluster analysis, and other advanced techniques will be covered. The focus of this class is hands-on learning of how to use these techniques to solve business problems using the appropriate software.
BAN 500 Descriptive Analytics (Graduate) This course covers statistical inference as applied to management decision making and focuses on building linear statistical models and developing skills for implementing statistical analysis in real situations. Applications require the use of statistical analysis programs on the computer.
BAN 502 Predictive Analytics (Graduate) This course explores computer-intensive methods for model selection, parameter estimation, and validation for predictive analytics. The course focuses on techniques and algorithms from the statistical and machine learning disciplines, and has a strong programming component. Example topics that could be included in this course include: ordinary least squares regression, logistic regression, classification and regression trees, neural networks, support vector machines, naive Bayes, principal components analysis, cluster analysis, and regularization. Each technique is accompanied with a focus on application and problem-solving.
BAN 592 Sports Analytics (Graduate) This course introduces fundamental analytics concepts in the context of sports. A variety of sports, professional and amateur, are covered with an emphasis on using analytics techniques and tools to add value and fuel competitive advantage. Software tools will be used extensively to illustrate concepts. A version of this course is also taught at the undergraduate level.
MBA 515 Business Analytics (Graduate) n introduction to data driven decision making using descriptive, predictive and prescriptive Business Analytics approaches. Topics included are data visualization, predictive techniques, data mining, simulation, optimization models, and decision analysis.
IMB 515 Business Analytics (Undergraduate) This course is the International MBA version of MBA 515.