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.

This program requires an average of 8–16 months to complete. Students may begin the program in the fall, spring, or summer term.

Learning Outcomes

• 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.

Admissions Information

For current admissions information, please visit the Metropolitan College website.

Degree Requirements

A total of eight courses (32 units) is required, distributed as follows:

Core Courses (four courses/16 units)

• MET AD 571 Business Analytics Foundations*
• MET AD 599 Introduction to Python and SQL for Business Analytics
• MET AD 632 Financial Concepts
• MET AD 715 Quantitative and Qualitative Decision-Making

*MET AD 571 is a prerequisite for all ABA elective courses and should be taken early in the degree program.

Elective Courses (three courses/12 units)

Choose three courses (12 units) from the list below, with approval from an academic advisor.

• MET AD 616 Enterprise Risk Analytics
• MET AD 654 Marketing Analytics
• MET AD 688 Big Data and Cloud Analytics for Business
• MET AD 698 Applied Generative AI for Business Analytics
• MET AD 699 Data Mining for Business Analytics
• MET AD 799 Deep Learning for Business Analytics
• MET AD 899 Capstone Project in Applied Business Analytics

General Elective (one course/4 units)

One elective in the area of management or data science chosen with the advice and approval of an academic advisor. Some courses may have additional prerequisites.

Master’s Thesis Option (two courses/8 units)

Students have the option to complete a master’s thesis in addition to the program’s eight course (32 unit) requirements. The thesis must be completed within 12 months and is available to master’s candidates who have completed at least five courses toward their degree and have a GPA of 3.7 or higher. Students are responsible for finding a thesis advisor and a principal reader within the department. The advisor must be a full-time faculty member; the principal reader may be a part-time faculty member with a doctorate. Permission must be obtained by the department.

• MET AD 800 Master’s Thesis 1
• MET AD 801 Master’s Thesis 2