Business Analytics (JHU Carey, MS Business Analytics/Information Systems, 2018-current)

This is a graduate-level course focusing on learning the basics of analytics (predictive, prescriptive) and applying those methods to real-world problems. The course is taught mainly using R and Excel

Being a business leader in a data driven world requires the knowledge of both data-related (statistical) methods and of appropriate models to use that data. The Foundations of Business Analytics course focuses on the latter: it introduces students to quantitative (“analytical”) frameworks and techniques for decision making. At a high level, these techniques include optimization, risk modeling, and Monte Carlo simulation. For each methodology students are first exposed to the basic mechanics, and then apply the methodology to real world business problems using software.

Emphasis will be not on programming, but rather on formulating problems, translating those formulations into useful models, and interpreting and presenting results. While a number of software programs are available, this course leverages the capabilities of MS Excel (However, students are welcome to use their preferred software packages such as R, Matlab or Python).

This course will not produce experts at modeling and/or programming (although students may be able to pick up a few spreadsheet skills along the way). Rather, the goal is to prepare managers who are comfortable translating trade-offs into models, understanding the output of the software, and who are appreciative of quantitative approaches to decision making. The course requires basic knowledge of calculus, algebra, statistics, as well as basic MS Excel knowledge. No programming knowledge is expected.