Data Science, M.S.
This course may be taken prior to or during the same term.
|Degree:||Master of Science (M.S.)|
|Department:||Mathematics & Statistics|
Building 4, Room 223
|College:||Hal Marcus College of Science and Engineering|
|Semester Hours Required For Degree: 30|
The M.S. in Data Science (M.S.D.S) offers students who hold bachelor’s degrees in mathematics, statistics, computer science, engineering, business, health or related fields an opportunity to broaden their knowledge in the field of data science. Data Science is an interdisciplinary field consisting of mathematics, statistics, computer programming, data management, machine learning, and visualization. Data scientists are trained to capture, maintain, process, and analyze data from large and complex data. Students in the M.S.D.S. program will learn to extract and communicate meaningful information from data sets and become capable of communicating their findings in a way that positively affects decisions in business, healthcare, industry, government, and the defense industry. Graduates with the ability to understand and use big data are already being employed by institutions and industries including government, healthcare, scientific research facilities, and colleges and universities. Students who graduate with the M.S.D.S. will be able to manipulate, manage, and interpret data suitable to the employer's needs. The M.S.D.S. program is designed for students seeking careers in science, industry, or government; or for students who plan to pursue doctoral studies.
In addition to the University graduate admission requirements described in the Admissions section of the catalog, the applicant must meet the following minimum departmental admission requirements for regular admission:
- have obtained a Bachelor’s degree from an accredited institution.
- have a minimum of 3.0 GPA (B or better average) on the undergraduate credits.
- Graduate Record Examination (GRE): Verbal score of at least 150 and Quantitative score of at least 150. GRE scores older than 5 years prior to admission may not be accepted.
If an applicant does not meet the above requirements, they may be considered for conditional admission. Please contact the department for more information.
- An applicant may be fully admitted if the student has all required undergraduate proficiency courses.
- An applicant may be provisionally admitted subject to completing the required undergraduate proficiency courses.
With the approval of the department, a maximum of six credit hours may be transferred into the program.
Prerequisite Course Requirements
Students seeking the M.S. in Data Science must have completed the following courses below prior to admission: