The Master of Science in Data Analytics program provides students with the ability to develop algorithms and computer programs for discovery of information from large amounts of data. This includes the architecture of programs, as well as technical details of algorithm development. Students are expected to be able to write and maintain novel computer programs that make efficient use of cutting-edge computer technology.
CURRICULUMThe MS in Data Analytics requires 30 credit hours and includes a project, which is a culminating experience. Students must receive a grade of "B" or higher in all courses.
|Total Credit Hours Required:|
Credit Hours Minimum beyond the Bachelor's Degree|
An undergraduate degree in computer science, statistics, computer engineering or information technology is desirable but not required. Applicants without a strong undergraduate background in computer science or statistics must demonstrate an understanding of the material covered in the following upper division undergraduate courses:
- COP 3330 Object-Oriented Programming
- COP 3503C Computer Science II
- COP 4710 Database Systems
- STA 2023 Statistical Methods I
- Programming experience or STA 4164 Statistical Methods III
Required Courses—24 Credit Hours
All students are required to take the following courses, for a total of 24 credit hours.
- CAP 5610 Machine Learning (3 credit hours)
- CNT 5805 Network Science (3 credit hours)
- COP 5711 Parallel and Distributed Database Systems (3 credit hours)
- COP 6526 Parallel and Cloud Computation (3 credit hours)
- STA 5206 Statistical Analysis (3 credit hours)
- STA 5703 Data Mining Methodology I (3 credit hours)
- STA 6704 Data Mining Methodology II (3 credit hours)
- CAP 6942 Project in Data Analytics (3 credit hours)
Restricted Elective Courses—6 Credit Hours
All students are required to complete 6 credit hours of approved electives that are selected after consultation with the student's adviser.
- CAP 6307 Text Mining I (3 credit hours)
- CAP 6315 Social Media and Network Analysis (3 credit hours)
- CAP 6318 Computational Analysis of Social Complexity (3 credit hours)
- CAP 6545 Machine Learning Methods for Biomedical Data (3 credit hours)
- CAP 6737 Interactive Data Visualization (3 credit hours)
- STA 6714 Data Preparation (3 credit hours)
Independent LearningThe Independent Learning Requirement is met by successful completion of a capstone project in CAP 6942 Project in Data Analytics.
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.
The College of Engineering and Computer Science strongly encourages prospective applicants to request a free pre-screening (www.cecs.ucf.edu/prescreen) of their qualifications prior to submitting an online application for graduate admission. However, a pre-screening is not required; rather, it is offered as a courtesy to all prospective applicants before they commit to submitting a complete online application and paying an application processing fee.
Admissions decisions are made on the basis of a complete online application only, and not on the basis of any pre-screening. Prospective applicants who are encouraged to apply to their intended graduate program based on the information provided for their pre-screening are not assured of admission or financial assistance when they submit a complete online application. Although it is possible, it is not likely, that prospective applicants who are discouraged from formally applying to a graduate program at the pre-screening stage will be admitted if they elect to submit a complete online application anyway.
In addition to the general UCF graduate application requirements, applicants to this program must provide:
- One official transcript (in a sealed envelope) from each college/university attended.
- Official, competitive GRE score taken within the last five years.
- Letters of recommendation (encouraged but not required)
Faculty members may choose to conduct face-to-face or telephone interviews before accepting an applicant into their research program.
An undergraduate degree in Computer Science, Statistics, Information Technology, or Computer Engineering is desirable but not required. Applicants without a strong undergraduate background in Computer Science and Statistics must demonstrate an understanding of the material covered in upperdivision undergraduate courses listed under the Articulation Section of the Curriculum Information. Applicants may choose to demonstrate their knowledge of these courses by taking these courses as non-degree seeking and scoring "B" or better in all of them.
|Data Analytics MS||
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International Transfer Applicants
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*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.
Graduate students may receive financial assistance through fellowships, assistantships, tuition support, or loans. For more information, see the College of Graduate Studies Funding website
, which describes the types of financial assistance available at UCF and provides general guidance in planning your graduate finances. The Financial Information
section of the Graduate Catalog is another key resource.
Fellowships are awarded based on academic merit to highly qualified students. They are paid to students through the Office of Student Financial Assistance, based on instructions provided by the College of Graduate Studies. Fellowships are given to support a student’s graduate study and do not have a work obligation. For more information, see UCF Graduate Fellowships, which includes descriptions of university fellowships and what you should do to be considered for a fellowship.