Data Science for Business Applications

Catalog description

Introduction to the process of extracting information and answers from multi-dimensional datasets to generate business insights. It will provide a broad overview of the entire data analytics pipeline, from data collection and preprocessing, to storing, exploring, visualizing, modeling, and interpretation. Modern computing tools (e.g., R, SAS) and essential data mining, machine learning, text, and network analytic methods will be discussed. Must be enrolled in CoBA. Prerequisite(s): Undergraduate level MIS 3000 Minimum Grade of D and BUS Tier II Complete 11 (the following must be completed: ACC 2010, 2020; EC 2040, 2050; EC 1050 or MTH 2280; ENG 1100, 2100; FIN 2210; MKT 2500; MS 2040, 2050) Course Level: Undergraduate Schedule Type(s): Lecture Grade Mode: Standard