Jim Downey, PhD: Department Chair
Telephone: (501) 450-5327 | Email: jdowney@uca.edu
Michael Ellis, PhD: Graduate Program Coordinator
Telephone: (501) 450-5322 | Email: mellis@uca.edu
[1] Objectives
The Graduate Certificate (GC) in Data Analytics is designed to meet the needs of students who work (or will work) with managing, using, and exploiting data in organizations. Effectively managing and using data in any organizational context is complex, and any certificate or degree program by necessity can focus only on specific aspects of such an endeavor. This certificate program introduces students to managing data, describing data, and using data for predictive and prescriptive purposes. It examines the critical thinking and experimental design process involved in data collection and analysis. The program is designed for almost any type of organizational manager, in any discipline, who wishes to more fully understand how to manage and use organizational data.
[2] Admission Requirements
In addition to the Graduate School admission requirements, a student may be admitted to the GC in Data Analytics program by fulfilling the following requirements:
- A bachelor’s degree from an accredited institution
- An undergraduate cumulative GPA of at least 2.70, or 3.00 in last 60 credit hours.
- A minimum 3.00 GPA on any graduate work (from anywhere)
- A current professional résumé that specifies the applicant’s professional experience in business
- College credit for a statistics (or business statistics) course
Note: The Graduate Certificate in Data Analytics requires its own application for admission. It may, however, also be completed in conjunction with either the MBA or MAcc. Both of these programs have elective hours that may be used to complete the GC-DA. See the information provided in Graduate Bulletin for either the MBA or MAcc for further information on completing the certificate while enrolled in one of these degree programs.
[3] Program Requirements
To earn the GC in Data Analytics, the student must complete twelve (12) hours of graduate-level course work, as specified below. A cumulative GPA of 3.0 is required.
Prerequisite Course (3 credit hours)
Take the following two courses (6 hours)
MIS 5381 Data Mining and Applied Analytics
Take two of the following five courses (6 hours)
MIS 5330 Prescriptive Analytics
MIS 6325 Predictive Analytics
MIS 6335 Python for Data Analytics
MIS 6365 Data Warehousing and Data Management
[4] Course Links
Follow this link for MIS course descriptions: course link.
Follow this link to the Undergraduate Bulletin for QMTH course descriptions: course link.