Bachelor of Applied Science - Computer Information Systems Technology, Data Science Specialization
Previous Degree Required: A.S./A.A.
Eligible for Financial Aid: Yes
Delivery Method(s): On-Campus, Hybrid
Location(s): Melbourne, Online
Additional Limited Access Application Process Required: No
Program Testing Requirements: Not Required
Academic Community: STEM
Program Code: CTBSDSBS
Classification of Instructional Programs (CIP) Code: 11.0401
Florida Department of Education CIP Code: 1101104011
The Data Science specialization within the Computer Information Systems Technology Bachelor of Applied Science degree his program prepares students for mid-level positions in this expanding fioueld. Students will gain a fundamental understanding of Data Science through courses that include Database Design and Architecture, Database Systems with Big Data, Data Mining, Numerical Analysis, Data Structures and Algorithm Analysis and an understanding of the key role of data security.
Refer to the Bachelor Degree Programs overview page to find information about admission, graduation, general education and other requirements. Students who need technical electives will work with a bachelor’s advisor to determine the courses best suited to their plan of study.
Visit the program page for more information.
Specialization Requirements
| Code | Title | Credit Hours |
|---|---|---|
| Associate Degree | ||
| Complete Associate Degree | 60 | |
| General Education or Technical Concentration | ||
| General Education (for A.S. degree students) or Technical Concentration (for A.A. degree students) | 21 | |
| Computer Information Systems Technology - Major Courses | ||
| GEB 3213 | Foundations of Managerial Communications | 3 |
| ISM 3011 | Introduction to Information Technology Management | 3 |
| ISM 4300 | Information Systems Operations Management | 3 |
| MAN 4504 | Operational Decision Making | 3 |
| Data Science Specialization | ||
| CAP 4770 | Data Mining | 3 |
| CAP 4773 | Capstone Project - Data Management Science | 3 |
| COP 3530 | Data Structures and Algorithm Analysis | 3 |
| STA 3024 | Statistics 2 for Data Scientists | 3 |
| Data Science Specialization Electives (Choose 15 credits) | 15 | |
| Database Systems with Big Data | ||
| Data Science Internship | ||
| Object Oriented Programming | ||
| Database Design and Architecture | ||
| Information Systems Analysis and Design | ||
| Applications in Information Security | ||
| Total Credit Hours | 120 | |
- Satisfy the foreign language competency requirement
- Satisfy the civic literacy competency requirement
Important Note: Computer Information Systems Technology has two Common Program Prerequisites. hese courses must be completed with a grade of "C" or higher before being admitted to 3000 - 4000 level courses.
- COP 2334 Introduction to C++ Programming
- STA 2023 Statistics
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Click on the course number to see course prerequisites. MAC 2311 will be accepted in place of STA 2023. Any Computer Programming course with a COP prefix will be accepted in place of COP 2334. No other course substitutions are permitted for either course.
Course Sequence
The following sequence is recommended. However, courses may not be offered in this order, so it is important that you work with an advisor to plan your schedule based on your specific needs.
| Term 1 | Credit Hours | |
|---|---|---|
| COP 3530 | Data Structures and Algorithm Analysis | 3 |
| GEB 3213 | Foundations of Managerial Communications | 3 |
| ISM 3011 | Introduction to Information Technology Management | 3 |
| Technical Elective 1 | 3 | |
| Credit Hours | 12 | |
| Term 2 | ||
| CAP 4770 | Data Mining | 3 |
| ISM 4300 | Information Systems Operations Management | 3 |
| MAN 4504 | Operational Decision Making | 3 |
| Technical Elective 1 | 3 | |
| Credit Hours | 12 | |
| Term 3 | ||
| STA 3024 | Statistics 2 for Data Scientists | 3 |
| Technical Elective 1 | 3 | |
| Credit Hours | 6 | |
| Term 4 | ||
| Technical Electives 1 | 12 | |
| Credit Hours | 12 | |
| Term 5 | ||
| Technical Electives 1 | 12 | |
| Credit Hours | 12 | |
| Term 6 | ||
| CAP 4773 | Capstone Project - Data Management Science | 3 |
| Technical Elective 1 | 3 | |
| Credit Hours | 6 | |
| Total Credit Hours | 60 | |
- 1
Students must select 15 credits from the following list: CAP 3783 Database Systems with Big Data, CAP 3940 Data Science Internship, COP 3330 Object Oriented Programming, COP 3703 Database Design and Architecture, ISM 3113 Information Systems Analysis and Design, and ISM 3324 Applications in Information Security. Students are required to take 6 additional technical elective credits.
Learning Outcomes
- Apply techniques and tools to visualize data in order to explore trends and patterns.
- Core Ability Supported: Process Information
- Apply techniques to clean data that is incomplete or missing.
- Core Ability Supported: Process Information
- Apply existing algorithms to make predictions and find patterns in data.
- Core Ability Supported: Think Critically and Solve Problems
- Demonstrate the ability to modify/design algorithms that use a linked-list based data structure
- Core Ability Supported: Think Critically and Solve Problems
- Demonstrate oral and presentation skills necessary to present data-driven results that tell a narrative applicable to the values and goals of the audience.
- Core Ability Supported: Communicate Effectively