Master of Science

M.S. in Data Science Online

Learn to expertly analyze data and provide counsel.

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The first fully online master’s in data science in Florida

Prepares graduates with the knowledge, skills and attitude needed to manipulate, manage and interpret data

Equips graduates to work in data science or begin a doctoral degree

Data Science, M.S. Overview

The University of West Florida’s fully online Master of Science in Data Science provides you with the tools to bridge data science with disciplines such as information technology, computer science, environmental science, business and healthcare. With their experience, graduates can pursue lucrative and fast-growing careers.

Our program offers synchronous coursework and one-on-one communication with expert faculty. You will also collaborate with graduate students from other disciplines as you tailor your curriculum to suit your career goals.

Throughout the data science degree program, develop sought-after techniques including statistical analysis, mathematical processes, regression modeling, multivariate methods, machine learning, database management and mining, and big data analytics. These skills will enable you to produce reports, presentations and graphics that positively influence business decisions and trends.

Using your M.S. in Data Science, you could work in institutions and industries including government, businesses, finance, healthcare, public or private scientific research and academia.

Select a Program Track

The program offers three tracks to prepare learners for in-demand data science careers.

Analytics and Modeling

In this track, students will learn to design data modeling processes and create algorithms and predictive models to solve complex problems. They’ll develop fluency in computational skills and proficiency in mathematics and statistics. With a focus on machine learning, software development, data storage and analysis and more, this track prepares learners for careers as statisticians, data engineers and project managers, among other careers that demand a mastery of statistics, programming and data structures.

Analytics of Business Decisions

Students who choose this track will master how to use data to make business decisions, solve problems and improve efficiency. The coursework equips students with knowledge of statistical tools and programming, mathematical and statistical algorithms and operation management. Students will be ready to implement changes, communicate results and work with various departments to make data-driven decisions.

Health Analytics

In the health analytics track, students gain proficiency in the statistical skills needed in the healthcare industry. Learners will be trained to manage and analyze health data to address public health issues. Coursework in this track prepares students to interpret complicated data sets, use statistical and computing tools and visualize data to communicate findings. Graduates can become clinical informatics analysts, project managers in the healthcare field and more.

Candidates for This Program Include:

Those pursuing a doctoral degree in data science, computer science or a related field
Students seeking to expand their experience with interdisciplinary technical, analytical and communication skills
Full- or part-time workers pursuing career advancement

You Will Be Able To:

Leverage data and information to help businesses make better strategic choices
Communicate and interpret complex data to varied audiences
Develop data-driven solutions for a business or organization

Courses and Requirements

Once prerequisite requirements are satisfied, the master’s in data science includes 21 core credit hours plus 9 elective credit hours. You can use elective courses to tailor your curriculum to industries including computer science, business, earth and environmental sciences, biology and health information.

: STA 2023 - Elements of Statistics
3 Credit Hours
Elements of Statistics
Prerequisite: MAC 1105* OR MAC 1105C* OR MAT 1033* OR MGF 1106* OR MGF 1107* OR 22 ACT Math OR 520 SAT Math OR 123 PERT Math STA2023 covers descriptive statistics, elementary probability theory, and basic statistical procedures, estimation, and inference. In addition to provide basic concepts in the mentioned areas it prepares the student for other more advanced statistical courses that are necessary for research. Meets General Education requirement in Mathematics. Meets Gordon Rule Applied Mathematics Requirement.
MAC 2311 - Calculus I
4 Credit Hours
Calculus I
Differential and Integral Calculus of Algebraic, Trigonometric, and Transcendental functions of single variables. Related applications. Meets General Education requirement in Mathematics. Meets Gordon Rule Theoretical Mathematics Requirement. Pre: MAC 1147 OR (MAC 1105 AND MAC 1114) OR (MAC 1114 AND MAC 1140) OR (MAC 1105C AND MAC 1114)
One programming course (such as Python)
: STA 5176 - Statistical Modeling
3.0 Credit Hours
Statistical Modeling
A second course in statistics for students in the Mathematical Sciences Graduate Program. Topics covered include analysis of variance, regression analysis, nonparametric statistics, contingency tables. Students will use matrix algebra to derive some properties of regression diagnostics, in addition to using the method of least squares to derive optimal estimators in linear models. This course is offered concurrently with STA 4173; graduate students will be assigned additional work.
STA 6235 - Modeling in Regression
3.0 Credit Hours
Modeling in Regression
Several advanced topics in regression are covered, such as nonlinear regression, influence diagnostics, Eigensystem analysis of X?X matrix, logistic regression, ridge regression, robust regression, and generalized linear models. Prerequisite: STA 5176
STA 6257 - Advanced Statistical Modeling
3 Credit Hours
Advanced Statistical Modeling
"This course will cover advanced statistical models, enabling students to model various discrete and continuous outcomes. The focus will be determined by instructor and may include such analyses as generalized linear analysis, nonlinear regression analysis, or spatial cluster analysis. In addition to advanced models, the course will include model constructions, model fi t, interpretation of results, and dissemination of results."
: Analytics and Modeling (21 credit hours)
Choose four courses from the following:

CAP 6789 - Advanced Big Data Analytics
3 Credit Hours
Advanced Big Data Analytics
In this course students study advanced methods to handle and analyze very large data sets in Hadoop's Big Data environment. Students work with the Spark architecture in the MapReduce framework. Students also learn to apply machine learning algorithms in Spark.
Prerequisite: CAP 6597 AND COP 5725
COP 5725 - Database Systems
3 Credit Hours
Database Systems
This course provides an introduction to database systems and database management system architectures. Students will discuss various database models with emphasis on the relational model and relational database design. The course also includes case applications using fourth-generation languages such as SQL.
MAP 6114 - Machine Learning
3 Credit Hours
Machine Learning
Machine learning uses interdisciplinary techniques such as statistics, linear algebra, optimization and computer science to create automated systems that can shift through large volumes of data at high speed to make predictions or decisions without human intervention. MAS3105 and the ability to program algorithms in a language of Matlab or Python are required before taking the course.
STA 6707 - Multivariate Methods
3.0 Credit Hours
Multivariate Methods
This course provides some of the concepts and methods of Multivariate analysis in order to describe and analyze multivariate data. Students will be introduced to multivariate extensions of Chi-Square and t-tests; discrimination and classification procedures; applications to diagnostic problems in biological, medical, anthropological and social research; multivariate analysis of variance; factor analysis and principal components analysis.
CAP 6771 - Data Mining
3 Credit Hours
Data Mining
The course addresses methods to discover patterns and trends in large datasets. With the aid of contemporary data mining software, students will apply the theoretical skills they acquire in the course to go through the complete data mining process starting from data pre-processing and cleaning, concept hierarchy generation, attribute relevance analysis to frequent itemset mining and association rule mining. Traditional methods such as Bayesian decision theory as well as modern approaches in classification and unsupervised clustering will be covered as well. Prerequisite: COP 5725
Students may choose 9 credit hours of any combination of 5000/6000-level technical electives approved by the College of Science and Engineering advisor. A minimum of 15 credit hours toward the program must be 6000-level courses.

Analytics of Business Decisions (21 credit hours)
Choose four courses from the following:

ISM 5404 - Business Intelligence Applications
3.0 Credit Hours
Business Intelligence Applications
Business Intelligence Applications uses various information technologies to identify, locate, acquire, transform, visualize and analyze business data in an effort to create new data products within an organizational context. The focus of the course is on using methodologies from design science to create new data products for management use in decision making. Offered concurrently with ISM 4117; graduate students will be assigned additional work. Graduate student status is required.
ISM 6136 - Big Data Mining: A Managerial Perspective
3.0 Credit Hours
Big Data Mining: A Managerial Perspective
Covers the new management paradigm of data-driven decision making from both a technology and managerial perspective. Principles of big data and data mining will be discussed in class lectures and employed through assignments and projects. Prerequisite: QMB 6305
GEB 5872 - MBA Foundations: Financial Management I**
1.5 Credit Hours
MBA Foundations: Financial Management I**
A course in the Accelerated MBA Foundations Series in which students are introduced to the accounting process of analyzing, measuring, and reporting business activity. Explores the precise language, assumptions, concepts, principles, and logic patterns inherent in the analysis and measurement of business activity. Describes the form and content of major financial statements. Briefly introduces the recording and reporting process used by accounting systems and examines basic financial reporting issues.
GEB 5875 - MBA Foundations: Management Skills and Applications*
1.5 Credit Hours
MBA Foundations: Management Skills and Applications*
Covers the historical evolution of management, organizational design, motivation, team building, leadership, change management, culture, strategic planning, and critical implementation/control elements critical to successful management and strategy. Social responsibility, ethics, globalization, and futures are also stressed.
MAN 6511 - Operations Management Problems
3 Credit Hours
Operations Management Problems
Planning and control of domestic and multinational service and manufacturing operations utilizing information inside and outside the organization. Techniques to plan and improve location, layout, flow through the facility, design of work, and management of the human factor; all with an emphasis on management and maintenance of quality. Contains a portfolio project.
ACG 6309 - Accounting for Decision Making
3 Credit Hours
Accounting for Decision Making
Upon completion of the course, students will gain knowledge about budgeting, profit planning, and controlling aspects of business decision making. This course covers three broad areas: fundamental financial and managerial concepts; revenue and cost accumulation techniques; and revenue and cost analysis. Available to non-accounting majors only.
Students may choose 9 credit hours of any combination of 5000/6000-level technical electives approved by the College of Science and Engineering advisor. A minimum of 15 credit hours toward the program must be 6000-level courses.

* GEB 5872 and GEB 5875 are 1.5 SCH; must take both courses.
** GEB 5872 must be taken before ACG 6309.

Health Analytics (21 credit hours)
Choose four courses from the following:

BSC 5459 - Bioinformatics and Data Science
3.0 Credit Hours
Bioinformatics and Data Science
This project-based course explores concepts and practical applications in bioinformatics. It covers essential topics such as data organization, representing and reasoning about sequence data, simple data mining strategies, and ethical protocols for data collection. Students will learn how to apply data science principles to biological, clinical, and public health problems to effectively work with large data sets, format data, and design applications to help visualize, analyze, interpret, and communicate the resulting insights in ways that advance science. Students will further examine current events demonstrating how collaborative, cross-disciplinary teams use bioinformatic technologies and tools with big data analytics to support translational research. Open to students from any discipline.
PHC 6000 - Epidemiology for Public Health Professionals
3.0 Credit Hours
Epidemiology for Public Health Professionals
This foundational course covers the application of epidemiologic procedures to the understanding of the occurrence and control of conditions such as infections and chronic diseases, mental disorders, community, and environmental health hazards, accidents, and geriatric problems in human populations. The course is critical to developing student competency in the foundational and practical utilities of epidemiology as a tool for disease surveillance and outbreak investigations, disease prevention and treatment. Part of the Master of Public Health degree program.
PHC 6251 - Disease Surveillance and Monitoring
3.0 Credit Hours
Disease Surveillance and Monitoring
Disease surveillance and monitoring is the systematic collection, analysis, interpretation, and dissemination of data for use in prioritizing, planning, implementing, and evaluating health programs, activities and practices in the United States as well as in other developed and developing countries. We will focus on these fundamental processes and procedures which are utilized to investigate and track infectious and communicable diseases as well as non-infectious chronic diseases. The course will highlight the importance of designing and reporting quantitative and qualitative contents in disease surveillance.
HSA 6197 - Health Informatics
3.0 Credit Hours
Health Informatics
This course discusses the multifaceted, interdisciplinary nature of health informatics. Topics covered include computer applications in medicine, health data classification and coding and legal and ethical issues (including documentation, security and regulatory requirements). Additional avenues for further credentialing will be covered.
HSA 6752 - Quantitative Foundations and Data Analysis for Health Admin
3.0 Credit Hours
Quantitative Foundations and Data Analysis for Health Admin
This course will introduce the methods for description and analysis which provide healthcare professionals with useful tools for making sense from data. The course will cover how healthcare data is dependent on analysis, categorization, and management.
HSA 6385 - Quality Improvement Processes in Health Organizations
3.0 Credit Hours
Quality Improvement Processes in Health Organizations
This course provides an overview of methods to improve health care systems and healthcare delivery using quality improvement theories and frameworks to execute an improvement project. Students will learn to focus on identifying opportunities to improve processes, developing methods to identify factors that affect process, and using data to determine appropriate actions.
PHC 6194 - GIS Applications in Public Health
3.0 Credit Hours
GIS Applications in Public Health
An online course providing hands-on training in the use of geographic information systems for public health-related data. Students will complete projects covering the collection, analysis, and visualization of spatial data using both public domain and commercial software tools supporting geospatial data. Through a set of focused case studies, students will learn the basic features and limits of each tool, as well as interoperability with other GIS software products (both public domain and commercial packages). Part of the Master of Public Health degree program.
Students may choose 9 credit hours of any combination of 5000/6000-level technical electives approved by the College of Health advisor. A minimum of 15 credit hours toward the program must be 6000-level courses.

Admission Requirements

To be considered for admission into the University of West Florida’s online master’s in data science program, you must have an undergraduate degree from an accredited institution. Other criteria for successful admission include:

An earned Bachelor’s degree from an accredited institution
A minimum of 3.0 GPA (B or better average) on undergraduate credits

If an applicant does not meet the above requirements, they may be considered for conditional admission. Please contact the department for more information.

An applicant may be fully admitted if the student has all required undergraduate proficiency courses.
An applicant may be provisionally admitted subject to completing the required undergraduate proficiency courses.

How to Apply

To apply for admission to this program, you first need to submit an application for graduate admission (plus a $30 application fee) and be accepted for admission into the University of West Florida. Review application deadlines. In addition, you must:

Submit official transcripts confirming a bachelor’s degree from an institution whose accrediting agency is included on the list of UWF approved accrediting agencies

Have questions about this program or the admissions process? Contact our graduate admissions team at gradadmissions@uwf.edu.

Costs & Financial Aid

Component	Cost	Total*
In-State Tuition	$384.60 per credit hour	$11,538.00
In-State Tuition with Maximum Transfer Credits (Up to 6)	$384.60 per credit hour	$9,230.40
Full Out-of-State Tuition	$1,044.24 per credit hour	$31,327.20
90% Out-of-State Tuition Waiver	$478.83 per credit hour	$14,364.90

Tuition waivers cover up to 90% of the non-resident portion of your tuition and are available to non-Florida residents (including international students) admitted to online campus programs and registered for online courses in active pursuit of that degree or certificate. You must pay all other assessed tuition and fees. Review Tuition Waiver Information to learn more.

Time to completion varies by student, depending on individual progress and credits transferred, if applicable. Fees are charged per semester unless otherwise noted. This program takes up to 24 months to complete, depending on transfer credits.

Refer to UWF Cost of Attendance Estimates and Financial Literacy for more information on UWF costs and financial aid.

* Tuition and fees are subject to change.

Alabama Differential Out-of-State Tuition

Residents of Alabama are eligible for Alabama Differential Tuition, a reduced out-of-state tuition rate. For more information and to verify residency status for tuition purposes, new undergraduate students should contact the Office of Undergraduate Admissions and new graduate students should contact the Graduate School. Current enrolled students should contact the Office of the Registrar.

Active Duty Military

All active-duty members of the U.S. military who are residing or are stationed outside the state of Florida shall have all (100%) out-of-state fees waived by the university. Contact the Military & Veterans Resource Center to apply for the Active Duty Military Out-of-State Waiver.

UWF Short-Term Financial Assistance

The University of West Florida provides eligible students with an alternative to paying the full amount of tuition at the beginning of each term in the form of an installment payment plan or a short-term loan.

Military Students

UWF is a Military FriendlyⓇ School proudly serving active-duty U.S. military members and veterans. As UWF has been a participant in the Yellow Ribbon Program since 2011, you could be eligible to receive free tuition with your military benefits.

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Financial Aid

Funding your college education should not empty your wallet. We offer various financial aid options for our online students, including loans, scholarships and grants for degree-seeking students.

Learn More About Financial Aid

Frequently Asked Questions

: You may either contact your enrollment counselor or log into your MyUWF account to view the status of your application.
: No, you may be enrolled part-time and be eligible for financial aid. Different awards have different enrollment criteria. For example, federal direct loans require at least half-time enrollment. All students are awarded assuming full-time enrollment. If you change enrollment plans, the Office of Financial Aid and Scholarships must be notified immediately, and we will revise your award if necessary.
: UWF will only accept credits from institutions whose accrediting agency is included on the list of UWF approved accrediting agencies, and the amount of transfer credits allowed depends on the program. For detailed information, visit our Transfer Students page.
: Refer to UWF Cost of Attendance Estimates for more information.