Applied Data Analytics (MS)
Description
Master of Science in Applied Data Analytics
Detroit Mercy's Master of Science in Applied Data Analytics is a 30 credit-hour program that is designed to uniquely position graduates as employment ready in a growing and versatile field. From e-commerce, to business, to government, to health care, organizations are turning to data science to understand their customers, improve efficiency and deliver targeted results. Detroit Mercy’s program is unique in its emphasis on the application of knowledge and skills in the area of data analytics.
Data analytics makes meaningful and useful inferences out of large data sets. to reveal trends and metrics that would otherwise be lost in the mass of information. This information can then be used to optimize the overall efficiency of a process, business or system. The ability to act on data lags far behind the ability to collect and store data, which is why data analytics professionals are in high demand.
Detroit Mercy’s curriculum is interdisciplinary and includes courses from several departments and colleges including Cybersecurity & Information Systems, Computer Science, Economics, Architecture, Business Administration, Mathematics and Health Professions. The capstone project, completed under the supervision of program faculty, provides a formative and interactive learning experience. Students will explore a dynamic range of courses. Upon completion of the program, students will be able to sift through mountains of data to extract simple relationships and use these data-informed decisions to identify new opportunities for an organization and approach information collection and analysis from an ethical viewpoint.
Whether you want to advance your knowledge or enhance your career with a graduate degree, Detroit Mercy’s Master of Science in Applied Data Analytics is a flexible program with online or on-campus options backed by faculty expertise. It is ideal for students around the world who are looking for a competitive advantage in an in-demand field.
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Degree Requirements - Master of Science in Applied Data Analytics (30 credits)
To obtain the Master of Science in Applied Data Analytics, a candidate must successfully complete a minimum of 30 credit hours of required graduate level courses including a capstone project. The program consists of eight required courses (24 credit hours) and two electives (six credit hours).
Required Courses (24 credits):
- CIS 5550 Database Design (3 credits) / DATA 5550 Database Design (3 credits)
- CIS 5560 Database Management (3 credits) / DATA 5560 Database Management (3 credits)
- CYBE 5800 Data Mining (3 credits)
- DATA 5001 Science and Data (3 credits)
- DATA 5060 Advanced Statistics for Applied Data Analytics (3 credits) OR MTH 5270 Applied Probability and Statistics (3 credits)
- DATA 5130 Capstone Project (3 credits)
- ECN 5150 Quantitative Foundations for Data Analysis (3 credits) / DATA 5150 Quantitative Foundations of Economic Analysis (3 credits)
- ECN 5800 Economic Modeling for Data Analysis (3 credits)
Electives - Select two courses (6 credits): Please consult with your academic advisor before making the selection as there are many more courses available. The following is only a list of sample electives.
- CIS 5010 Introduction to Information Systems (3 credits)
- CIS 5400 Software Management (3 credits)
- ECN 5400 Financial Economics (3 credits)
- ECN 5480 Business Forecasting (3 credits) / DATA 5480 Business Forecasting (3 credits)
- ECN 5640 Financial Economics II (3 credits)
- DATA 5070 Statistical Software Packages for Applied Data Analytics I (3 credits)
- DATA 5080 Statistical Software Packages for Applied Data Analytics II (3 credits)
- DATA 5600 Topics in Applied Data Analysis (3 credits)
- INT 5200 Data Mining and Reporting in Intelligence (3 credits)
- HSA 5500 Information Systems for Health Services Administration (3 credits)
- MTH 5270 Applied Probability and Statistics (3 credits)
- MTH 5590 Mathematical Modeling (3 credits)
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Capstone Project Guidelines
Students pursuing the Master of Science in Applied Data Analytics must complete the 30 credit-hour program with a capstone project (DATA 5130). This is a three credit-hour course with a variable credit-per-semester setup. Students must register a total of three credit hours to complete the project. Students have the flexibility to take the capstone project over a few semesters or in a single term. For example, a student could register for one credit hour in a fall term, one credit in the winter term and one credit in the summer term of a given academic year. Alternatively, a student could register for one credit hour in the fall term and two credit hours in the winter term (or vice versa). Last, a student could simply register for all three credit hours in a single term. The capstone is not graded but rather is evaluated on the basis of successful completion of the three credit hours. Students may register one credit per term (i.e. winter, fall) and will draw upon their areas of interest. Students in their first year are recommended to start exploring potential project topics in consultation with the academic advisor and other faculty members in the program and complete the project over two consecutive terms. See the Capstone Project Guidelines for more information.
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Admission Requirements
Prerequisites and Admission Requirements
In order to be admitted to the Master of Science in Applied Data Analytics program, an applicant must meet Detroit Mercy’s entrance requirements. The applicant must also have completed a baccalaureate or advanced degree from a regionally accredited college or university with a cumulative GPA of 3.0 or better. In certain cases, additional prerequisites may be required.
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STEM/OPT Program - International Students
The Master of Science in Applied Data Analytics program is classified as a STEM program by the U.S. Department of Homeland Security. International students who attend the on-campus program have the opportunity to apply for an extended Optional Practical Training (OPT) using the Classification of Instructional Programs (CIP) code 11.0802.
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Course Delivery & Tuition
To provide greater convenience and flexibility, this program is available:
- Onsite with traditional day and evening in-classroom formats on the Detroit Mercy McNichols Campus*
- Online. This program can be taken completely online**
* Please see the Detroit Mercy Graduate Tuition and Fees schedule for domestic and international students.
** Please see the Detroit Mercy Graduate Tuition and Fees schedule for graduate online programs.
Program Contact Information
Yu Peng Lin, Ph.D.
Professor and Chair
Department of Economics
Briggs Building, Room 323
McNichols Campus
Email: linyp1@udmercy.edu
Telephone: 313-993-1096
Fax: 313-993-1166