Bachelor of Science, Data Analytics (Program Description)

Print Degree Planner (opens a new window) |

Total Degree Credits: 120

See the Bachelor of Science, Data Analytics (Plan of Study)

The Data Analytics program at Florida Polytechnic University affords students the opportunity to learn the foundational scientific and mathematical principles of analyzing complex data sets. The program offers concentrations in Advanced Topics, enabling students to explore different facets of the field, or in more specific concentrations such as Big Data Analytics, Cloud Virtualization, and Health Informatics. The program’s blend of computer science, statistics, and mathematics prepares students to succeed in a wide range of career and professional industry sectors.

Program Educational Objectives

The objectives of the Data Analytics program is to produce graduates who will do the following:

Excel in careers or advanced study in data analytics, computer science, and related fields;
Achieve leadership positions in technology fields;
Pursue life-long learning and professional development and contribute meaningful to society.

Student Outcomes

Graduates of the Data Analytics program will demonstrate the ability to do the following:

Apply critical thinking and problem solving techniques to identify and solve a problem.
Apply statistical methods and procedures to model a problem, design an experiment to measure a solution, and collect and analyze data to evaluate the solution.
Execute Project Management skills including planning, designing, evaluating and implementing a project plan to achieve a determined set of results.
Coordinate and collaborate in a team environment to analyze a problem, design a solution, evaluate the solution, and implement the solution if feasible, specific to the student’s concentration

College Skills (1) & Co-Curricular

All majors are required to complete an approved internship/professional experience prior to graduation.

SLS 1106 - First Year Experience Credits: 1
IDS 4941 - Professional Experience Internship Credits: 0

General Education (38)

Click here to view the complete list of General Education offerings. The State of Florida requires a minimum of 36 credit hours of general education for the baccalaureate degree. The following are required for the B.S. in Data Analytics.

Communication (6)

ENC 1101 - English Composition 1: Expository and Argumentative Writing Credits: 3
ENC 2210 - Technical Writing Credits: 3

Arts and Humanities (3 to 6)

ARH 2000 - Art Appreciation Credits: 3
PHI 2010 - Introduction to Philosophy Credits: 3
IDS 2144 - Legal, Ethical, and Management Issues in Technology Credits: 3

Social Sciences (6 to 9)

Data Analytics majors select 12 credits from Art and Humanities and Social Sciences. Students may opt to take 9 credits in Social Science and 3 in Arts and Humanities, or divide them evenly. Six credits, as noted below, must be taken in Social Sciences.

Required for DA majors:
ECO 2023 - Principles of Microeconomics Credits: 3
Required, one from the following:
AMH 2010 - American History to 1877 Credits: 3
AMH 2020 - American History Since 1877 Credits: 3
AMH 2930 - Special Topics in American History Credits: 3
Additional available credits, OR another History, OR another Arts and Humanities:
ECO 2013 - Principles of Macroeconomics Credits: 3
PSY 2012 - General Psychology Credits: 3

Mathematics (8)

MAC 2311 - Analytic Geometry and Calculus 1 Credits: 4
MAC 2312 - Analytic Geometry and Calculus 2 Credits: 4

Natural Sciences (12)

CHM 2045 - Chemistry 1 Credits: 3
CHM 2045L - Chemistry 1 Laboratory Credits: 1
PHY 2048 - Physics 1 Credits: 3
PHY 2048L - Physics 1 Laboratory Credits: 1
PHY 2049 - Physics 2 Credits: 3
PHY 2049L - Physics 2 Laboratory Credits: 1

Advanced Math and Analytics (12)

STA 2023 - Statistics 1 Credits: 3
MAD 2104 - Discrete Mathematics Credits: 3
MAS 3114 - Computational Linear Algebra Credits: 3
QMB 3200 - Advanced Quantitative Methods Credits: 3

Data Analytics Core (48)

These courses provide an essential foundation in Data Analytics.

IDS 1380 - Introduction to STEM Credits: 3
COP 2271C - Introduction to Computation and Programming Credits: 3
EGN 1007C(x) - Concepts and Methods for Engineering and Computer Science Credits: 1
CIS 2005 - Fundamentals of Applied Information Credits: 3
COP 2272C - Computer Programming 1 Credits: 3
COP 3353C - Introduction to Unix Credits: 2
COP 3710 - Database 1 Credits: 3
COP 4415 - Data Structures Credits: 3
CDA 3100 - Computer Architecture Credits: 3
CNT 3004C - Introduction to Computer Networks Credits: 3
COP 3834C - Web Application Development Credits: 3
CTS 2375 - Cloud Implementation Strategies and Cloud Providers Credits: 3
COP 4531 - Algorithm Design & Analysis Credits: 3
CIS 4320 - Design Science Credits: 3
CEN 4010 - Software Engineering Credits: 3
CNT 4403 - Data Security Credits: 3
CAP 4612 - Machine Learning Credits: 3

Concentrations (12)

Students choose twelve credits from one concentration area.

Advanced Topics

Students choose from courses in any concentration and/or from the list of Data Analytics electives.

Data Analytics Electives (3)

Choose three credits from the list below or from available concentration courses.

CIS 3301 - Business Intelligence Credits: 3
CNT 3200 - Distributed Information Systems Credits: 3
COP 3330C - Computer Programming 2 Credits: 3
COP 3729C - Database 2 Credits: 3
COP 4520 - Introduction to Parallel and Distributed Computing Credits: 3
COP 4610 - Operating Systems Concepts Credits: 3
ECP 4031 - Benefit Cost Analysis Credits: 3
EGS 3625 - Engineering & Technology Project Management Credits: 3
ENT 2112 - Entrepreneurial Opportunity Analysis Credits: 3
HIM 2340 - Development and Administration of Health Information Systems Credits: 3
HIM 4654 - Implementation of EHR/EMR and Clinical Support Methods Credits: 3
HIM 4016 - Policy Issues in Health Informatics Credits: 3

Program Capstone Sequence (6)

CAP 4733 - Senior Capstone 1: Systems Acquisition, Integration, and Implementation Credits: 3
CDA 4910 - Senior Capstone 2: Directed Research Credits: 3