Master of Science in
Master of Science in Data Analytics
College of Engineering and Computer Science
College of Sciences
There is an increasing need to turn large and complex amounts of data into knowledge to drive business decisions. Companies are looking for people with the technical skills to manipulate, manage, and interpret data. Become an expert in the fast-growing field of analytics to see the big (data) picture.
What is the UCF MS in Data Analytics?
The MS in Data Analytics is a 30 credit hour interdisciplinary program that prepares students to develop algorithms and computerized systems to facilitate the discovery of information from large amounts of data. It will utilize the technical aspects of big data analytics, including algorithm design, programming, acquisition, management, mining, analysis, and interpretation of data.
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What will you learn?
- Use state-of-the-art software tools to perform data mining and analysis on large structured and unstructured data sets, and transform such data into knowledge.
- Design and implement new algorithms for data mining and analysis, and study their time-, space-, and energy-efficiency.
- Perform data acquisition and management for extremely large and dynamic databases.
- Present and communicate knowledge derived from data in an unambiguous and convincing manner.
- 30 credit hours to completion
- Completion in 16 (full time option) or 20 months
- Face to Face instruction, offering convenient evening and weekend classes
- Taught by UCF Faculty with strong connections to Data Analytics
- Cohort model for strong peer support
- Courses are offered two per semester
- International Students are eligible for paid internships via the UCF Office of Experiential Learning
- International Students are eligible for Optional Practical Training (OPT) status after graduation
Course of Study
Electives (must choose 2):
- Text Mining I (CAP 6307*)
- Social Media and Network Analysis (CAP 6315*)
- Computational Analysis of Social Complexity (CAP 6318*)
- Interactive Data Visualization (CAP 6737*)
- Data Preparation (STA 6714*)
- Machine Learning Methods for Biomedical Data (CAP 6545*)
* Sample Syllabus, provided as an example only!
Help companies use large amounts of data in innovative ways.
Job titles associated with this field:
Data Scientist Data Analyst Data Architect Data Engineer Data Mining Specialist Business Intelligence Analyst Big Data Engineer Big Data Scientist Database Administrator
I am currently an Assistant Professor at University of Central Florida. Before coming to UCF, I worked with Professor Jinchi Lv and Professor Yingying Fan as a postdoctoral research associate at USC Marshall School of Business. I received Ph.D. in Statistics from University of Manchester in 2011.
The requirements for admission include an undergraduate degree, official GRE/TOEFL scores, a resume, letters of recommendation (encouraged but not required) and the demonstration of understanding in fundamental concepts. The program’s director, assisted by the program’s faculty, will evaluate student applications. Face-to-face or telephone interviews may be conducted for admission. The details of the admission requirements are as follows:
Applicants must have earned a bachelor’s degree from an accredited institution with a GPA of 3.0 or better. One official transcript (in a sealed envelope) is required from each college/university attended.
Official, competitive GRE and TOEFL (if applicable) scores taken in the last five years must be provided with the application. At the discretion of the program director, conditional admission can be granted with pending GRE scores.
Working Knowledge of Fundamental Concepts
Applicants without a strong undergraduate background in Computer Science or Statistics must demonstrate an understanding of the material covered in the following undergraduate courses:
- COP 3503 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
Understanding of these concepts can be demonstrated by a combination of the following:
- Taking these courses; OR
- Convincing the program director that the student work experience covers these materials; OR
- Having taken these courses at UCF or equivalent courses at another institution; OR
- At the recommendation of the program director, registering in the statistics Bridge Course, the Computer Science Bridge Course or both. These 4-week bridge courses are free.
Tuition & Fees
Total Program Cost
*(Includes credit hours, fees, and administrative costs. Textbooks not included.)