Track Description
The Master of Science in Statistics and Data Science, Data Science track focuses on data analytics and its application to business, social, and health problems.
The Data Science track in the Statistics and Data Science MS program focuses on data analytics and its application to business, social, and health problems.
The program is particularly suited for individuals who have completed an undergraduate program in mathematics, statistics, economics, business, or other related fields, and wish to pursue a career in data science. Data scientists analyze massive data sets to uncover trends and associations, and make theoretically sound decisions on, for example, business, social, and health subjects. Data scientists have one of the most coveted jobs, as the demand for them far exceeds the existing number of qualified persons in the area. Currently, the work force in the data science industry consists mainly of individuals trained with post college education. To date, very few university degree programs exist for training students for such a large and growing industry in the United States.
Curriculum
The Data Science track in the Statistics and Data Science MS program is composed of 24 credit hours of required courses and 12 credit hours of restricted electives. Students must also pass a comprehensive written examination.
Total Credit Hours Required: 36 Credit Hours Minimum beyond the Bachelor’s Degree
Required Courses: 24 Credit Hours
Note: STA 5703 and STA 6704 both require research projects that fulfill the independent learning requirement for the program.
Elective Courses: 12 Credit Hours
Select electives from the following courses. No more than one COP course can be selected.
Comprehensive Examination
All students must take a comprehensive written examination covering the five courses STA 6326 , STA 6327 , STA 5104 , STA 6714 and STA 6238 . For full-time students, this examination will normally be taken just prior to the start of the second year of their graduate work. Students are allowed two attempts to pass the exam. Failure to pass after the second attempt will result in dismissal from the program.
Independent Learning
STA 5703 and STA 6704 both require research projects that fulfill the independent learning requirement for the program. Both courses require students to build models for target variables of projects with very large sets of data, write a report, and then give an oral presentation on their independent learning experiences.
Application Requirements
For information on general UCF graduate admissions requirements that apply to all prospective students, please visit the Admissions section of the Graduate Catalog. Applicants must apply online. All requested materials must be submitted by the established deadline.
In addition to the general UCF graduate admission requirements , applicants to this program must provide:
- One official transcript (in a sealed envelope) from each college/university attended.
- Official, competitive GRE or GMAT score taken within the last five years.
- NOTE: The GRE has been removed as an admission requirement for this graduate program for applicants applying Spring 2021 through the Fall 2021 term. This is a temporary measure in response to disruptions caused by the COVID-19 pandemic.
- Résumé.
- Applicants applying to this program who have attended a college/university outside the United States must provide a course-by-course credential evaluation with GPA calculation. Credential evaluations are accepted from World Education Services (WES) or Josef Silny and Associates, Inc. only.
Applicants not qualified for regular graduate status may be initially admitted to the university in non-degree-seeking status and later admitted to regular status once all deficiencies have been eliminated, although only nine hours of graduate course work taken as a non-degree-seeking student can count toward a graduate degree.
Meeting minimum UCF admission criteria does not guarantee program admission. Final admission is based on evaluation of the applicant’s abilities, past performance, recommendations, match of this program and faculty expertise to the applicant’s career/academic goals, and the applicant’s potential for completing the degree.
Application Deadlines
| Data Science |
*Fall Priority |
Fall |
Spring |
Summer |
| Domestic Applicants |
Jan 15 |
Jul 1 |
Dec 1 |
Apr 1 |
| International Applicants |
Jan 15 |
Jan 15 |
|
|
| *Applicants who plan to enroll full time in a degree program and who wish to be considered for university fellowships or assistantships should apply by the Fall Priority date. |
Return to: