MS in Applied Business Analytics
The Master of Science (MS) in Applied Business Analytics program provides comprehensive coverage of data analytics concepts, techniques, and state-of-the-art tools used in the process of data-driven business decisionmaking. Students have the opportunity to gain hands-on experience with a variety of analytical models and decision-support tools and to apply them to interlinked data-inputs and large data sets in the areas of marketing, operations, product and technology innovations, financial services, and others. The curriculum covers advanced software tools and functions such as descriptive, predictive, and prescriptive modeling, text and data mining, visual analytics, and business simulations. Graduates of the program will be able to analyze data-driven business processes, select appropriate analytical methods to monitor and identify performance issues, prescribe possible outcomes, and propose optimal data-based solutions.
- The knowledge and skills to better utilize available information in operational, tactical, and strategic decisionmaking in organizations.
- Experience with various powerful emerging technologies and techniques for increasing the value of both in-house and third-party data sets.
- An understanding of how organizations are using interlinked data-inputs, analytics models, and decision-support tools to better understand their operations, customers, and markets.
- Expertise in web analytics and metrics, and the ability to procure and process unstructured text, and delve into hidden patterns within data sets.
- The ability to facilitate knowledge discovery using data-mining and visualization techniques over vast amounts of data.
For current admissions information, please visit the Metropolitan College website.
As a prerequisite to the course MET AD 571 Business Analytics Foundations, students are required to complete the AD 100 Pre-Analytics Laboratory (online). Some courses may have additional prerequisites. Please note that MET AD 571 Business Analytics Foundations is a prerequisite for all four specialization courses and should be taken early in the degree.
A total of 10 courses (40 credits) is required, distributed as follows:
Core Courses (four courses/16 credits)
- MET AD 571 Business Analytics Foundations
- MET AD 605 Operations Management: Business Process Fundamentals
- MET AD 632 Financial Concepts
- MET AD 715 Quantitative and Qualitative Decision-Making
Specialization Courses (four courses/16 credits)
- MET AD 616 Enterprise Risk Analytics
- MET AD 654 Marketing Analytics
- MET AD 688 Web Analytics for Business
- MET AD 699 Data Mining for Business Analytics
Elective Courses (two courses/8 credits)
Choose two additional related graduate MET courses, with the approval of an advisor, to enhance your individual management interests or to work toward a certificate.
No grade lower than B– may be applied toward degree, certificate, or diploma requirements. Students earning below a 3.0 cumulative grade point average (GPA) will be placed on academic probation status. Students on academic probation must make satisfactory progress toward achieving a minimum of 3.0 by the following semester, and must be in a position to graduate with a 3.0 or better within the remaining program courses. While grades of B or B– are considered passing, these grades will not assist in raising an unsatisfactory GPA to a satisfactory level. Therefore, students must obtain a minimum grade of B+ during a probation period.
Students who, in the determination of the department and based on past student performance, are not in a position to raise their GPA to the necessary level to graduate within the remaining courses will be dismissed from the program. Students who have not removed themselves from academic probation status after one semester for full-time status or three courses for part-time status will be dismissed from the program.
Second Master’s Degree Option
In appreciation of the converging needs of management and technology, the departments of Actuarial Science, Administrative Sciences, and Computer Science collaborate to offer a unique opportunity to students currently enrolled in their degree programs as well as alumni of those programs. Learn more.