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This course focuses on the art of communicating ideas embedded in data through visual means. Students are introduced to industry-standard graphic and data design techniques used to create understandable visualizations in order to communicate effectively with a particular audience. Techniques in organizing and articulating data are developed using real world examples. The course materials, assignments and project will all be prepared using the R programming language and Tableau software.

This course will introduce students to foundations of relational database design and management with a focus on business domains and business analytics applications. Topics include database design principles, entity-relationship diagrams, constructing queries in SQL, connecting, updating, and analyzing databases -- critical skills for data analysts. The course materials, assignments and project will all be prepared using the R and SQL programming language.

The course consists of applied training in foundational topics for supervised learning such as Linear Regression, Nearest Neighbors and Neural Networks. It first builds a sound understanding of data preparation, exploration and reduction methods. It covers both prediction as well as classification processes. The emphasis is on understanding the application of a wide range of modern machine learning techniques to specific decision-making situations across business domains, rather than on mastering the mathematical and computational foundations of the techniques.

The focus of this course is on statistical and data analytical methods for the preparation of business forecasts. A variety of empirical techniques are covered: smoothing methods, moving averages, regression analysis, classical time-series decomposition methods, and ARIMA (Box-Jenkins) models. Emphasis is placed upon building forecasting models and evaluating their reliability. The focus is on time-series data. R is the preferred statistical package; Tableau and other packages will be introduced as time permits.

The University of New Haven offers a wide variety of in-depth courses that create a transformational educational experience for our students. To view the complete list of courses you'll take while pursuing a M.S. in Business Analytics, check out the Academic Catalog:

Whether you're still in high school or are transferring from another college, we offer full- and part-time opportunities for undergraduates from inside the U.S. and abroad. The admission process can begin as early as the end of your high school junior year.

The Application Process

We offer a comprehensive financial aid program, with students receiving assistance in the form of grants, scholarships, student loans, and part-time employment. Funds are available from federal and state governments, private sponsors, and from university resources. More than 85 percent of the University's full-time undergraduate students receive some form of financial assistance.

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