Introduction to Enterprise Analytics

Catalog description

Introduces advanced specific analysis techniques—including forecasting, simulation, linear programming, regressive modeling, and optimization—as well as the Python programming language. The more advanced mathematical, statistical, and presentation functions within the R library packages are heavily utilized. Emphasizes enterprise data analytics, which is the extensive use of data, statistical, and quantitative analysis; exploratory and predictive models; and fact-based decision making to drive business strategies and actions. Course projects embrace marketing, retail, financial, and human resources analytics, as well as familiarize students with general industry practices. Emphasizes end-to-end analytic development skills, including data management, data engineering, analytics modeling, and strategy development. Offers students hands-on opportunities to apply quantitative techniques in strategic business decision making.