Data Science Specialization - Computer Information Systems Technology, Bachelor of Applied Science
Previous Degree Required: A.A./A.S.
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:
Academic Community: STEM Science, Technology, Engineering, and Mathematics
Program Code: CTBSDSBS
Classification of Instructional Programs (CIP) Code: 11.0401
Florida Department of Education CIP Code: 1101104011
Students can only select one major and one specialization. Students may receive a specific A.S./BAS degree only one time. Students may take courses from multiple specializations, however, the degree will be awarded only once.
Eastern Florida State College prepares students for mid-level positions in this expanding field through the Data Science specialization within the Computer Information Systems Technology Bachelor of Applied Science degree.
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.
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) 1 | 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 | ||
COT 4500 | ||
Information Systems Analysis and Design | ||
Applications in Information Security | ||
Total Credit Hours | 120 |
- 1
The BAS in Computer Information Systems Technology has two Common Program Prerequisites. These courses must be completed before being admitted to 3000 and 4000 level courses and students will need to earn a grade of "C" or higher:
Students must take STA 2023 Statistics and COP 2334 Introduction to C++ Programming as part of their 21 General Education or Technical Concentration if they have not satisfied these program requirements with their associate degree.
Important Notes: The prerequisite for STA 2023 is MGF 1106 or MAC 1105 with a grade of "C" or higher. MAC 2311 is the alternate approved course to STA 2023. No other substitutions are permitted. The prerequisite for COP 2334 is COP 1000. The Common Program Prerequisite, COP 2334 may also be satisfied by any COP Computer Programming course. No other course substitutions are permitted
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, COT 4500 , 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: Data Science BAS
- 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 ability to design new algorithms to make predictions and find patterns in data not analyzable with existing algorithms.
- 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