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How can I demonstrate “working knowledge of fundamental concepts”?

Understanding of these concepts can be demonstrated by a combination of the following:

  1. Taking these courses. In case that your background or education have not provided you with fundamental concepts needed to success in the MSDA, the program coordinator will help you put together a plan of study to take few undergraduate courses in order to succeed in the MSDA program; OR
  2. Convincing the program director that the student work experience covers these materials. Your work experience should be clearly noted in your resume and you may be asked to clarify or expand on your work experience in your interview; OR
  3. Having taken these courses at UCF or equivalent courses at another institution as demonstrated by your transcripts; OR
  4. At the recommendation of the program director, taking the Statistics Bridge Course, the Computer Science Bridge Course or both. Students that need a short refresher in fundamentals can be conditionally accepted in the program pending taking and approving one or both of the Bridge courses. For example, if a student has taken statistics classes many years ago and in his professional work experience the student has not been involved in statistics, then the student may be required to take the Bridge course in statistics as a condition to be admitted in the MSDA.

Related FAQs

Previous approval of the course instructor, students currently employed can opt for fulfilling their internship requirement with their current employers.

If your GPA is below the minimum required 3.0, then you may be considered for provisional admission into the program at the discretion of the program director. Please keep in mind that the number of Provisionals that can be admitted is limited and we will not know what that number is until after the admissions deadline.

Yes, the GRE is not required.

No, the bridge courses are only for students accepted or conditionally accepted into the MSDA.

The TOEFL is require only for international students that are not native English speakers and that are first time students at an English speaking institution.

Admission decisions will be announced 2 weeks after the application deadline.

Having an undergraduate degree in Computer Science, Statistics, Computer Engineering, or Information Technology will in most cases be sufficient to fulfil this requirement. If student does not have a strong undergraduate background in Computer Science or Statistics the student must demonstrate an understanding of the material covered in the following undergraduate courses:

  • COP 3503C Computer Science II – Algorithms, Data Structures
  • COP 3330 Object-Oriented Programming – Object-Oriented Programming Concepts, Expression of Concepts in a Language
  • COP 4710 Database Systems – Relational Databases, Structured Query Language
  • STA 2023 Statistical Methods I – Probability Distributions, Data Organization
  • STA 4164 Statistical Methods III – Regression Analysis

Related fields include those that would provide a similar level of technical principles and discipline analogous to those required by a Computer Science or Statistics program. These include most other engineering disciplines, as well as mathematics, physics, quantitative management or other similar fields. Students with degrees in other disciplines such as business or economics will also be considered on a case-by-case basis, provided they have significant work experience and/or they take the four-week Bridge Courses offered for fundamental Computer Science and Statistics concepts.

Letters of recommendation are encouraged but not required. The letters of recommendation must explain the learner’s value as an employee or student, accomplishments, and personal qualities in an organizational or academic context.

All student admitted to the MSDA program are encouraged but not required to take these two bridge courses. Only students conditionally admitted with the express requirement of taking and approving one or both of these bridge courses are required to take them.

The letters are preferred to come from a current or former employer, academic advisor, former teacher or mentor. The individuals with whom you the learner had considerable professional or academic interaction should be selected. The selected individual must be able to attest to the learner’s value as an employee or student, accomplishments, and personal qualities in an industrial or academic context.

Yes, the capstone course “Project in Data Analytics (CAP 6942)” is structured to be an internship program. In this class students will earn credit while interning with an industry partner of the MSDA program. In this internship students will identify and solve a meaningful real world problem in Big Data.