ADVANCED PREDICTIVE ANALYTICS

Graduate

This course provides students with the ability to employ selected analytic techniques to solve business problems and effectively communicate the solution. A thorough knowledge of probability, mathematical statistics, selected models and methods for analyzing data is assumed. This course covers topics such as predictive model building process in R; problem definition, data visualization, exploratory data analysis, identification of data issues and resolution, and initial model selection; model selection; model validation; communication of results and uncertainties; sample project and report. A particular focus will be placed on communication of technical results for business applications, data exploration and feature selection, and model selection and construction. Graduate students are required to complete an additional project and report. This will be defined in consultation with the instructor to ensure the scope and assessment are sufficiently advanced to warrant graduate level credit. This course is cross-level listed with AMS 4610. Credit cannot be received for both MCS 8610 and AMS 4610. PREREQUISITE: Admission to a graduate program in Science HOURS OF CREDIT: 3