Graduate Certificate

Data Science Online Certificate

Thrive as an in-demand statistician, data analyst or business intelligence professional.

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Aligns with M.S. in Data Science coursework (with the option to later pursue that degree)

Learn advanced statistics, modeling and in-depth computational techniques

Excel in a rapidly growing and lucrative field

Data Science Certificate Overview

The University of West Florida’s fully online Data Science Certificate program provides you with the statistical, modeling and computational skills to pursue a career in data or elevate your current position. A wide range of high-paying, in-demand positions will be within reach. In the program, you’ll learn how data impacts society and your particular field. You’ll be able to raise critical questions about and learn methods for optimizing data, its interpretation and its visualization.

Working with data represents one of the most attractive and in-demand skill sets in business. Whether you’re an engineer, investor, mathematician, researcher or business professional looking to enter into or advance your career in data, this online Data Science Certificate program can meet your goals. It’s also versatile in the sense that when you graduate, you’ll have the option to seamlessly move into the master’s program in data science.

Candidates for This Program Include:

Graduate non-degree seeking students or students in a graduate degree program
Those who work in business and are seeking career advancement
Engineers, investors, mathematicians and researchers who use scientific computing or data analytics in their work

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

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

Courses and Requirements

UWF’s online Data Science Certificate program includes a total of 12 credit hours. It requires completion of the following courses with a grade of C or higher.

: STA 5126 - Statistics for Data Science I
3 Credit Hours
Statistics for Data Science I
Statistics for Data Science I is the first course in statistics for students in data science. This 8-week asynchronous online course builds the fundamentals of statistics necessary for students to perform and interpret appropriate hypothesis tests using softwares based on the data and research questions at hand. Offered concurrently with STA 4121. Graduate students will be assigned additional work including constructing professional reports.
STA 5232 - Statistics for Data Science II
3 Credit Hours
Statistics for Data Science II
Statistics for Data Science II is a second course in statistics for students in data science. This course covers the application of regression analysis techniques using softwares for statistical analysis. Broadly, students will learn how to construct statistical models and disseminate predictions and results to a wide audience. There will be a focus on choosing the appropriate modeling strategy for the data and research questions at hand. Offered concurrently with STA 4231. Graduate students will be assigned additional work including conclusions based on statistical inference.
CAP 5775 - Databases for Data Science
3 Credit Hours
Databases for Data Science
Organizations can generate copious amounts of data. Extracting useful knowledge from data warehouses for use in decision making can provide a competitive advantage for the organization by identifying strengths and weaknesses. In this course, students will learn how the data in data warehouses are organized, analyze the data through analytical queries, and apply machine learning algorithms to build predictive models. Offered concurrently with CAP 4774. Graduate students will be assigned additional work.
CAP 5756 - Tools for Data Science
3 Credit Hours
Tools for Data Science
An 8-Week course on tools for data science using R, Python, SQL, and Spark. Throughout the course, there will be hands-on exercises with computing resources. The course will include introductions to several packages in R, particularly Tidyverse, libraries in Python such as Pandas/NumPy/Statsmodels, SQL clauses and summary statistics, and Spark framework for distributed computing. Offered concurrently with CAP 4755. Graduate students will be assigned additional work.
: In addition to fulfilling two core requirements, students will choose to take two electives out of the following courses:

Choose two courses (six credit hours in total) from the following list. Selection is based on Hal Marcus College of Science and Engineering advisor approval. 6 hours

STA 5126 - Statistics for Data Science I
3 Credit Hours
Statistics for Data Science I
Statistics for Data Science I is the first course in statistics for students in data science. This 8-week asynchronous online course builds the fundamentals of statistics necessary for students to perform and interpret appropriate hypothesis tests using softwares based on the data and research questions at hand. Offered concurrently with STA 4121. Graduate students will be assigned additional work including constructing professional reports.
STA 5232 - Statistics for Data Science II
3 Credit Hours
Statistics for Data Science II
Statistics for Data Science II is a second course in statistics for students in data science. This course covers the application of regression analysis techniques using softwares for statistical analysis. Broadly, students will learn how to construct statistical models and disseminate predictions and results to a wide audience. There will be a focus on choosing the appropriate modeling strategy for the data and research questions at hand. Offered concurrently with STA 4231. Graduate students will be assigned additional work including conclusions based on statistical inference.
CAP 5775 - Databases for Data Science
3 Credit Hours
Databases for Data Science
Organizations can generate copious amounts of data. Extracting useful knowledge from data warehouses for use in decision making can provide a competitive advantage for the organization by identifying strengths and weaknesses. In this course, students will learn how the data in data warehouses are organized, analyze the data through analytical queries, and apply machine learning algorithms to build predictive models. Offered concurrently with CAP 4774. Graduate students will be assigned additional work.
CAP 5756 - Tools for Data Science
3 Credit Hours
Tools for Data Science
An 8-Week course on tools for data science using R, Python, SQL, and Spark. Throughout the course, there will be hands-on exercises with computing resources. The course will include introductions to several packages in R, particularly Tidyverse, libraries in Python such as Pandas/NumPy/Statsmodels, SQL clauses and summary statistics, and Spark framework for distributed computing. Offered concurrently with CAP 4755. Graduate students will be assigned additional work.
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.
MAP 5196 - Mathematics for Data Science
3 Credit Hours
Mathematics for Data Science
It is a course in linear algebra, vector calculus and probability illustrated on data science applications. While the emphasis will be on the mathematical concepts, a programming platform Matlab will be used for application demonstration.
ISM 6137 - Business Analytics
3.0 Credit Hours
Business Analytics
This course focuses on development of quantitative and analytical skills required to model, analyze, interpret and solve managerial decision making problems. Prerequisite: QMB 6305
ISM 6405 - Advanced Business Intelligence Applications
3 Credit Hours
Advanced Business Intelligence Applications
Advanced 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.
ISM 6136 - Big Data Mining: A Managerial Perspective
3 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.
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.
ISM 6562 - Advanced Business Data Management
3 Credit Hours
Advanced Business Data Management
Explores the complexities of data management in the digital world of big data. Uses advanced information technology and software tools to analyze data and create business intelligence. Integrates the strategies, policies, methodologies, techniques, and tools to solve problems and assist decision-making via business data management in firms
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.
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.
* GEB5872 and GEB 5875 are 1.5 SCH; must take both courses.

** GEB 5872 must be taken before ACG 6309.

Admission Requirements

To be considered for admission into the University of West Florida’s online Data Science Certificate program, you must be admitted into the University as a graduate non-degree seeking student. Other requirements include:

Have a B.S. degree with a grade point average of 3.0 or higher
Prior knowledge in statistics and basic programming is recommended for this certificate. If you do not have a strong background in statistics, start with an introductory statistics course, such as STA 2023 Elements of Statistics, before beginning this certificate.

How to Apply

Once accepted as a graduate non-degree seeking student, prospective students for this certificate must contact the graduate advisor from the Department of Mathematics & Statistics to start the Declaration of Certificate process before the drop/add period of the semester of completion, and to complete the online Graduate Certificate Declaration Form on MyUWF.

Have questions about this program or the admissions process? Contact our graduate admissions team at gradadmissions@uwf.edu. If you are a current UWF student, please reach out to the department academic advisor

Costs & Financial Aid

Component	Cost	Total*
In-state Tuition	$384.60 per credit hour	$5,769.00
Out-of-State Tuition	$1,044.24 per credit hour	$15,663.60
90% Out-of-State Tuition Waiver	$478.83 per credit hour	$7,182.45

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

Time to completion varies by student, depending on individual progress. Fees are charged per semester unless otherwise noted. This program takes up to 12 months to complete, depending on course availability.

* Tuition and fees are subject to change.

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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.

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.
: You must first be admitted to UWF and registered for the course(s). Enrolled students, visit UWF eLearning to access your course.
: Each year, Information Technology Services publishes computer purchase recommendations for students. They are designed to ensure greater product reliability, usability, quality, functionality, and support. Be aware that these recommendations are based on typical computing use.
: Refer to UWF Cost of Attendance Estimates for more information.