Data Science is an emerging discipline that seeks to infer insights from large amounts of data ("big data") by using various statistical techniques and algorithms. The discipline is concerned with both statistical techniques that measure the validity of such insights and with computational techniques for managing data and resources efficiently.
The Data Science B.S. is an interdisciplinary degree that is offered jointly by the Department of Computer Science, and School of Data, Mathematical, and Statistical Sciences. This program emphasizes the technical aspects of big data analytics, including algorithm design, programming, acquisition, management, mining, analysis, and interpretation of data. This program aims to train students to develop algorithms and computerized systems to facilitate the discovery of information from big data.
In addition to preparing graduates for immediate entry into careers and the job market, graduates of this program may also go on to pursue advanced degrees, such as the 麻豆原创 M.S. in Data Analytics program or a related M.S. degree, or a Ph.D. program in Computer Science, Statistics and Data Science or a related area, and graduates may also seek professional distinction.
Admission Requirements
Degree Requirements
- Students who change degree programs and select this major must adopt the most current catalog.
- With the exception of the Capstone course, co-op or internship credit cannot be used in this major. Students should consult with a program advisor.
- All prerequisites of courses taught within the College of Sciences and the College of Engineering & Computer Science will be enforced.
- Courses designated in the General Education Program (with the exception of prerequisite courses) may be spread over 4 years, and those designated in the Common Program Prerequisites section must be completed within the first 60 hours.
- Students must earn at least a "C" (2.0) in each advanced core required course for the major.
- Students must achieve a minimum cumulative GPA of 2.0 in all courses satisfying major requirements. Data Science students must have continual access to a computer. Contact the 麻豆原创 Technology Product Center or see the website (http://www.cstore.ucf.edu) for the minimum hardware and software specifications.
Degree Requirements
Core Requirements: Advanced Level
66 Total Credits
- Complete all of the following
- Basic core is met by courses specifically identified in the GEP and CPP. BSC2010C, COP3223C, MAC2311C, MAC2312, MAC2313, PHY2048C (PHY2048/PHY2048L), STA2023
- Complete the following:
- COP3502C - Computer Science I (3)
- CIS4340 - Data Management Technology (3)
- COP4283 - Data Science Programming (3)
- ISC4241 - Data Science I (3)
- ISC4242 - Data Science II (3)
- ISC4551 - Data Graphics and Visualization (3)
- MAS3105 - Matrix and Linear Algebra (4)
- STA4364 - Statistical Foundations of Data Science and Artificial Intelligence I (3)
- STA4365 - Statistical Foundations of Data Science and Artificial Intelligence II (3)
- STA4163 - Statistical Methods II (3)
- STA4164 - Statistical Methods III (3)
- STA4724 - Big Data Analytics Methods (4)
- Complete at least 1 of the following:
- COT3100C - Introduction to Discrete Structures (3)
- MHF3302 - Logic and Proof in Mathematics (3)
- Complete at least 1 of the following:
- CAP4611 - Algorithms for Machine Learning (3)
- ESI4312 - Deterministic Methods for Operations Research (3)
- MAP4112 - Mathematical Foundations of Machine Learning and Artificial Intelligence (3)
- STA4241 - Statistical Learning (3)
- Complete at least 1 of the following:
- ISC4311 - Predictive Analytics (3)
- STA4852 - Applied Time Series (3)
- Earn at least 19 credits from the following types of courses: Select from upper- division (3000-level or above) courses that are not used to satisfy another degree requirement, after meeting with a departmental advisor. The program encourages selection of courses from among those by the participating departments, but does not restrict electives to such courses.
Capstone Requirement
4 Total Credits
- Complete at least 1 of the following:
- ISC4323C - Praxis for Data Science (4)
- STA4942 - Internship in Data Science (4)
Grand Total Credits: 70
Total Undergraduate Credit Hours Required: 120
Foreign Language Requirements
Graduation
Departmental Exit Requirements
- All students will complete an exit interview.
- Students must earn at least a "C" (2.0) in each advanced core required course for the major.
- Students must achieve a minimum cumulative GPA of 2.0 in all courses satisfying major requirements.
University Minimum Exit Requirements
- A 2.0 麻豆原创 GPA
- 42 semester hours of upper division credit completed
- 30 of the last 39 hours of course work must be completed in residency at 麻豆原创.
- A maximum of 45 hours of extension, correspondence, CLEP, Credit by Exam, and Armed Forces credits permitted.
- Complete the General Education Program, the State Writing and Math Requirement, and nine hours of summer credit
Honors In Major
Application and admissions through The Burnett Honors College and SDMSS. More information about Honors in the Major can be found at https://honors.ucf.edu/research/.
Related Programs
- Actuarial Science (B.S.)
- Computer Science (B.S)
- Industrial Engineering (B.S.)
- Mathematics (B.S.)
- Statistics (B.S.)
- Actuarial Science Minor
- Business Minor
- Computer Science Minor
- Economics Minor
- Information Technology Minor
- Leadership Studies Minor
- Mathematics Minor
- Secure Computing and Networks Minor
- Statistics Minor
- Technological Entrepreneurship Minor
Advising Notes
- It is the student's responsibility to ensure they have satisfied course prerequisites before registering for a class. Students should consult with a program advisor.
- Contact your Academic Success Coach (ASC) in the College of Sciences Advising Services (COSAS) office (CSB 250) for more information about overall progress toward your degree, GEP and other university requirements, academic probation, special problems as well as general academic advising.
Transfer Notes
- Lower division courses do not substitute for upper division courses.
- Courses transferred from private and out-of-state schools must be evaluated for equivalency credit. The student must provide all supporting information.
- Submit your requests for course evaluations at https://sciences.ucf.edu/cosas/ and select Prospective Students > Transfer Course Evaluations.
- Courses transferred for equivalency to courses in the College of Engineering and Computer Science must be formally evaluated for equivalency by the relevant department.
- The following substitutions are acceptable for Common Program Prerequisites if taken as part of the AA course work.
- Computer Science: Any COP programming language course will satisfy the CPP. However, COP 3223C (Introduction to Programming with C) is a prerequisite for Computer Science courses and still needs to be taken; however COP 2220 (C Programming) will be substituted for COP 3223C.
Program Academic Learning Compacts
Program Academic Learning Compacts (student learning outcomes) for undergraduate programs are located at:
http://www.oeas.ucf.edu/alc/academic_learning_compacts.htm
