Analytics and Technology Degree (B.S., Minor)

Introduction to the fundamental ideas and techniques of computer programming. Introduction to topics such as variables, sequence, selection, repetition, and objects will be covered. Students will spend a significant amount of time out of class writing and debugging code in a programming language.

This course introduces students to the core concepts, processes, and tools of Business Intelligence. Lessons will introduce business process analysis (BPA) and cover the core business processes that business intelligence (BI) systems seek to address including finance and accounting, marketing, operations, and human resources. Further, this course explores the business use case of structure, unstructured and big data.

Students will be able to conduct and explain the basic concepts of data mining: supervised vs. unsupervised learning. Specifically, classification, k-means clustering and regression models will be emphasized. Students will learn the proper method and process of defining a data mining problem. Students will conduct analysis in terms of defining business programs and solving them with the appropriate methodology. Communication skills of models results to technical and non-technical audiences will be emphasized. Class will be conducted in R.

This course utilizes a series of prescriptive and predictive analytical tools such as forecasting, advanced regression, statistical process control, linear programming, network models and data mining to examine real-world business problems. Students will develop skills in defining a business problem, selecting the appropriate tool for solving the problem, and effectively communicating the results.