Optimization Simulation

Catalog description

Drawing upon previous coursework in predictive analytics, modeling, and data mining, this course provides a review of statistical and mathematical programming and advanced modeling techniques. It explores computer intensive methods for parameter and error estimation, model selection, and model evaluation. The course focuses upon business applications of statistical graphics and data visualization, tree-structured classification and regression, neural networks, smoothing methods, hybrid models, multi-way analysis, and hierarchical models. This is a case-study and project-based course with a strong programming component.