About this Program
³Ô¹Ï±¬ÁÏ's M.S. in Data Science and Analytics prepares students to build statistical models, apply machine learning tools, and extract insight from complex datasets across sectors, including technology, healthcare, finance, and government.
The program is offered online and on-campus in Norfolk, Virginia, through ³Ô¹Ï±¬ÁÏ's dedicated School of Data Science — one of the few standalone data science schools at a public R1 research university in the United States. Students choose from five concentration options and complete a capstone project using real-world data.
You learn to leverage data to identify trends and patterns, communicate results, and recommend optimal solutions. Moreover, you deepen your understanding of the discipline-specific scientific and theoretical concepts critical to modern data science and analytics.
Program Highlights
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³Ô¹Ï±¬ÁÏ is an R1 research university with active partnerships with NASA Langley Research Center, the Naval Research Laboratory, and Jefferson Lab — providing students access to real-world data science research that most graduate programs cannot offer.
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The School of Data Science, one of a small number of dedicated data science schools at U.S. public universities, provides a focused academic community, dedicated faculty, and industry connections in the mid-Atlantic region.
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Five concentration options let students specialize: Artificial Intelligence and Machine Learning, Business Intelligence and Analytics, Engineering and Big Data Analytics, Geospatial Analytics, or Physics.
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A capstone project integrates real-world datasets from business, science, engineering, or geospatial domains.
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The full program is available online through ³Ô¹Ï±¬ÁÏGlobal or on-campus in Norfolk, Virginia.
Data Science Concentrations
This concentration focuses on the design and application of machine learning models, neural networks, and AI systems. Students develop competency in deep learning frameworks and apply AI techniques to large-scale data problems in industry and research settings.
This concentration prepares students to translate data into business decisions. Coursework covers data warehousing, reporting systems, and analytical methods used across finance, retail, and operations environments.
This concentration addresses the technical challenges of large-scale data systems, including distributed computing, data pipelines, and high-volume data processing. It is suited to students pursuing careers in data engineering or technical analytics roles.
This concentration focuses on spatial data, geographic information systems (GIS), and location-based analysis. ³Ô¹Ï±¬ÁÏ's coastal and maritime research context makes this one of the few geospatial analytics concentrations in the region with direct ties to environmental and defense applications.
Designed for students with physics backgrounds, this concentration applies data science methods to physical systems, simulations, and scientific data analysis — reflecting ³Ô¹Ï±¬ÁÏ's research strengths through partnerships with Jefferson Lab and other national laboratories.
This concentration focuses on the design and application of machine learning models, neural networks, and AI systems. Students develop competency in deep learning frameworks and apply AI techniques to large-scale data problems in industry and research settings.
This concentration prepares students to translate data into business decisions. Coursework covers data warehousing, reporting systems, and analytical methods used across finance, retail, and operations environments.
This concentration addresses the technical challenges of large-scale data systems, including distributed computing, data pipelines, and high-volume data processing. It is suited to students pursuing careers in data engineering or technical analytics roles.
This concentration focuses on spatial data, geographic information systems (GIS), and location-based analysis. ³Ô¹Ï±¬ÁÏ's coastal and maritime research context makes this one of the few geospatial analytics concentrations in the region with direct ties to environmental and defense applications.
Designed for students with physics backgrounds, this concentration applies data science methods to physical systems, simulations, and scientific data analysis — reflecting ³Ô¹Ï±¬ÁÏ's research strengths through partnerships with Jefferson Lab and other national laboratories.
Featured Courses
Admissions Requirements
Students entering the Master of Science in data science and analytics program should meet the minimum University admission requirements for graduate admission, including submission of the following:
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- A and associated application fee.
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- A bachelor's degree from a regionally accredited institution in the United States, or an equivalent institution outside the United States, in a field that provides adequate preparation for graduate study in data science.
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- Official copies of transcripts of all regionally accredited institutions attended (or equivalent non-U.S. institutions).
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- A current resume.
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- Two letters of recommendation from individuals familiar with the applicant's professional and/or academic background.
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- A statement of professional goals.
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- International students should submit their current Test of English as a Foreign Language (TOEFL) scores to the ³Ô¹Ï±¬ÁÏ International Graduate Admission Office. We require scores of at least 230 on the computer-based TOEFL or 80 on the TOEFL iBT.
Careers and Outcomes
Data scientists, machine learning engineers, and business intelligence analysts are among the fastest-growing roles in the U.S. labor market. According to the , employment for data scientists is projected to grow 34% through 2033. This is far above the average for all occupations.
Check out these ideas from ³Ô¹Ï±¬ÁÏ's Center for Career & Leadership Development and the . A median salary is a midpoint of what people typically earn—half of those surveyed earned above the median salary, and half earned below.
Conduct research into fundamental computer and information science as theorists, designers, or inventors. Develop solutions to problems in the field of computer hardware and software.
Produce financial and market intelligence by querying data repositories and generating periodic reports. Devise methods for identifying data patterns and trends in available information sources.
Develop and implement a set of techniques or analytics applications to transform raw data into meaningful information using data-oriented programming languages and visualization software. ³Ô¹Ï±¬ÁÏ data mining, data modeling, natural language processing, and machine learning to extract and analyze information from large structured and unstructured datasets. Visualize, interpret, and report data findings. May create dynamic data reports.
Cost of Attendance
Tuition is charged per credit hour. Amounts shown are tuition only and do not include mandatory fees, technology-delivered course fees, course-specific fees, books, housing, meal plans, or other costs. Campus-based students may take technology-delivered or online courses. Tuition is based on student classification. Fees for technology-delivered courses and other costs are listed on the ³Ô¹Ï±¬ÁÏ tuition and fees page.
Ways to Fund Your Degree
There are a few ways for you to save on the cost of attending ³Ô¹Ï±¬ÁÏ, including scholarships, assistantships, and student loans. For more details about financial aid at Old Dominion, visit the Financial Aid Office page.
Prospective master’s students can look forward to funding opportunities that include:
- The Graduate School and Office of Research summer research awards, which are offered each year.
- The Dr. Hussein Abdel-Wahab Memorial Graduate Fellowship
Review our Graduate School resources for updated information on scholarships and assistantships.
Frequently Asked Questions
The M.S. in Data Science and Analytics at ³Ô¹Ï±¬ÁÏ is a graduate degree offered through the School of Data Science. Students choose from five concentration areas (Artificial Intelligence and Machine Learning, Business Intelligence and Analytics, Engineering and Big Data Analytics, Geospatial Analytics, or Physics) and complete a capstone project using real-world data. The program is available or on-campus in Norfolk, Virginia.
Yes. The full M.S. in Data Science and Analytics is available online through ³Ô¹Ï±¬ÁÏGlobal. Online students take the same courses, work with the same faculty, and earn the same degree as on-campus students. The is designed for working professionals.
Students from non-CS backgrounds may be considered if they demonstrate competency in the following core areas: statistics and probability, basic programming (C++ or Java), linear algebra, and calculus. Applicants who do not hold a degree in computer science, engineering, mathematics, or a related field should contact the School of Data Science admissions team to discuss their background before applying.
³Ô¹Ï±¬ÁÏ's School of Data Science has active research partnerships with NASA Langley Research Center, the Naval Research Laboratory, and Jefferson Lab. Graduate students may participate in funded research through the Graduate School and Office of Research summer research awards and the Dr. Hussein Abdel-Wahab Memorial Graduate Fellowship. The Virginia Beach Data Science Institute, a collaborative research space operated by ³Ô¹Ï±¬ÁÏ, hosts industry and government data science projects.
³Ô¹Ï±¬ÁÏ is accredited by the Southern Association of Colleges and Schools Commission on Colleges (SACSCOC) and is classified as an R1 doctoral research institution by the Carnegie Classification of Institutions of Higher Education.
Tuition costs vary by program and are subject to change. Visit the Current Tuition Rates page for the most up-to-date tuition information.
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