Mar 28, 2024  
2022-2023 Undergraduate Catalog & Student Handbook 
    
2022-2023 Undergraduate Catalog & Student Handbook [ARCHIVED CATALOG]

Bachelor of Science, Data Science (Program Description)


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Total Degree Credits: 120

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

 


Data Science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from data in various forms, both structured and unstructured. New computational and analytic approaches to a vast array of forms, scales, and sources of data are now critical to research, decision-making, and action.

Data scientists develop mathematical models, computational methods and tools for exploring, analyzing and making predictions from data. They ask appropriate questions about data and interpret the predictions based on their expertise of the subject domain.

The rigorous curriculum in Data Science program focuses on the fundamentals of applied mathematics, computer science, probability, statistics, optimization, and machine learning while incorporating real-world examples.

In addition to taking Data Science core curriculum subjects, students also complete a concentration in one of four areas: Big Data Analytics, Intelligent Mobility, or Quantitative Economics & Econometrics.

After completion of the B.S in Data Science, students will be able to:

1.     Analyze a complex computing problem and to apply principles of computing and other relevant disciplines to identify solutions.

2.     Design, implement, and evaluate a computing-based solution to meet a given set of computing requirements in the context of the program’s discipline.

3.     Communicate effectively in a variety of professional contexts.       

4.     Recognize professional responsibilities and make informed judgments in computing practice based on legal and ethical principles.

5.     Function effectively as a member or leader of a team engaged in activities appropriate to the program’s discipline.      

6.     Apply theory, techniques, and tools throughout the data science lifecycle and employ the resulting knowledge to satisfy stakeholders’ needs.

 

**Course offering frequency subject to change**


College Skills (1) & Co-Curricular


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

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. 

Arts and Humanities (6)


Data Science majors select 12 credits from Art and Humanities and Social Sciences. Students select 6 credits in Social Science and 6 in Arts and Humanities. Six credits, as noted below, must be taken in Art and Humanities.

Social Sciences (6)


Six credits, as noted below, must be taken in Social Sciences.

Concentrations (12)


Students select one concentration from Big Data Analytics, Health Systems Engineering, Intelligent Mobility, or Quantitative Economics & Econometrics for twelve credits.

Advanced Topics


Select 12 credits from Data Science elective and concentration courses. 

Big Data Analytics


Students in Big Data Analytics learn to collect, manage, and optimize large-scale structured and unstructured data sets to facilitate information and decision-making. Students in Big Data Analytics develop a strong foundation in essential programming skills, quantitative analysis, and hardware and software solutions for facilitating effective use of big data.

Quantitative Economics & Econometrics


Quantitative Economics and Econometrics focuses on quantitative analysis and rigorous modeling of economic phenomena. This includes analysis of individual and firm decisions when data is messy, incomplete, or otherwise imperfect, analysis of strategic situations, and analysis of market outcomes and trends. Training in Quantitative Economics and Econometrics hones critical reasoning skills and prepares students for analytical careers or for graduate or professional study.

Intelligent Mobility & Autonomous Systems


Intelligent Mobility uses data and technology to connect people, places, and goods across all transportation modes. Growth in intelligent mobility will transform the way people travel, interact with their environment, and connect goods and services.

Data Science Electives (3)


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

Program Capstone Sequence (6)


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