100% Online Graduate Data Science Degree
Take your career to the next level with the online Master of Science in Data Science from ÃÛÌÒ´«Ã½ Maryland. Designed for working professionals from all academic backgrounds, this program will prepare you with the skills you need for roles across industries like data scientist, business analyst, computer systems analyst, data mining analyst, and business intelligence specialist. This 100% online, full- or part-time master’s degree offers flexible scheduling and asynchronous options for busy professionals and career changers.
Be more – now is your opportunity to explore careers in the growing and in-demand field of data science.
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Program Overview
- Format: Full- or part-time, self-paced
- Location: 100% online, asynchronous
- Duration: 1-3 years
- Program Starts: Fall, Spring, Summer
Curriculum and Program
Data science is an interdisciplinary, in-demand field blending business, computer science skills, statistics, and programming. As a data scientist, you will gather and use data to perform predictive analyses for a range of organizations, businesses, and governments. Using disparate sources of data, you will build forecasts and provide actionable insights for decision-makers across fields such as marketing, healthcare, finance, research, and more.
With 100% online and self-paced classes, enjoy the flexibility of earning your graduate data science degree from anywhere, anytime. Full- and part-time options are available. Learn more and get your application fee waived by attending a free information session.
The M.S. in Data Science graduate program is 31-34 credits. Two specializations are available: Technical and Business Analytics. Electives are available in computer science, statistics, and business. Specific course descriptions are available in the Graduate Academic Catalogue.
Required Courses include:
- CS701 - Introduction to Programming (may be waived)
- CS703 - Programming for Data Science
- CS737 - Machine Learning (only Technical Specialization) (CS703)
- DS730 - Introduction to Data Science
- DS795 - Data Science Project Design (CS703, DS851, ST710)
- DS796 - Data Science Project (DS795)
- DS851 - Applied Machine Learning (DS730 or permission of the instructor)
- ST710 - Statistical Computing
- ST765 - Linear Statistical Models (ST710)
Save time and tuition expenses with Data Science’s accelerated option. Current undergraduate students can apply in their junior year and begin graduate coursework in their senior year. Undergraduates can take up to three graduate-level classes during their senior year.
Customize your experience by aligning your courses with your personal interests and career goals. All specializations are available to students in the online program. We currently offer two specializations.
| Technical | Business Analytics |
|---|---|
| 31-34 credits | 31 credits |
| The technical specialization focuses on providing additional training in computer science and machine learning. | The business analytics specialization allows for greater course flexibility allowing students to focus their degree towards data analytics. |
| CS701 - Introduction to Programming (may be waived) | CS701 - Introduction to Programming or Program Elective |
| CS703 - Programming for Data Science | CS703 - Programming for Data Science |
| ST710 - Statistical Computing | ST710 - Statistical Computing |
| DS730 - Introduction to Data Science | DS730 - Introduction to Data Science |
| DS851 - Applied Machine Learning | DS851 - Applied Machine Learning |
| DS795 - Data Science Project Planning | DS795 - Data Science Project Planning |
| DS796 - Data Science Project | DS796 - Data Science Project |
| ST765 - Statistical Research Methods | ST765 - Statistical Research Methods |
| CS737 - Machine Learning for Data Science | |
| Computer Science Elective | Program Elective |
| Statistics Elective | Program Elective |
| Program Elective | Program Elective |
Apply to the M.S. in Data Science
- Bachelor’s degree
- Online application
- Application fee (waived for Information Session attendees)
- Official transcripts
- Essay
- Resume
- Letter of Recommendation
- All foreign transcripts must be evaluated via an approved service. ÃÛÌÒ´«Ã½ the International Academic Records page for more information.
- Additional requirements may be necessary for international applicants.
ÃÛÌÒ´«Ã½ Maryland offers various financial resources to support your graduate journey, including awards, loan options, and assistantships. Merit-based scholarships are available to top-performing applicants and are awarded at the time of admission; no separate application process is required.
| Start Term | Application Deadline |
|---|---|
| Summer | May 1 |
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Fall |
August 1 |
| Spring | December 1 |
M.S. in Data Science Academics
The Master of Science in Data Science blends computer science and statistics courses to render students adaptable to any domain with rigorous statistical and computational skills. The program includes a data science core, which is at the nexus of business, computer science, and statistics. The curriculum integrates ethics as a fundamental tenet.
5-Course Core + 7 Additional Courses
Following the five-course core classes, you will take seven additional courses:
- Two statistics courses
- Two computer science courses
- One elective from business, statistics, or computer science
- A one-credit design course
- A capstone research project conducted with a partner in local industry, government, or non-profit organization
Two-Semester Practicum
Gain real-world experience through a required two-semester practicum, which may include a summer internship. The practicum is an independent or group project utilizing the data science techniques acquired during the program in an applied manner to solve a practical problem with a local partner.
SAS Certification
Earn the SAS certification, recognizing your ability to leverage SAS analytical tools for data preparation, analytics, and visualization. This is available to those currently enrolled in either the technical specialization or business analytics specialization.
Build Expertise for Tomorrow's Careers
Why ÃÛÌÒ´«Ã½ for Graduate Data Science?Graduates reported full satisfaction with the online format and faculty interaction in 2025 according to exit survey
Best online master's in data science for 2025 by TechGuide
Reported by graduates in 2025 according to exit survey
Ron Capute, '25
ÃÛÌÒ´«Ã½â€™s MS Data Science program offered a diverse array of topics and had plenty of advanced classes for those that preferred them. The instructors were very knowledgeable and available to help. I particularly enjoyed the true semester-style cadence with a structured curriculum.
Chase Green, '26
I would recommend ÃÛÌÒ´«Ã½ because the program aligns with current industry knowledge and builds upon the skills needed to succeed in today's data-driven environment.
Mark Granatire, '26
It's a program that allows you gain knowledge and experience with tools and techniques currently being used in the real world.
Steve Eisner, '26
Every member of faculty seemed truly passionate and knowledgeable and frequently made themselves available to support the work.
Program Outcomes
According the to the U.S. Bureau of Labor Statistics, over the next decade. With the flexibility and customizable coursework of the 100% online M.S. in Data Science, now is the time to get hands-on, project-based experience to upskill in your current role or pursue a new career.
Careers
ÃÛÌÒ´«Ã½'s data science students graduate qualified and prepared for roles including:
- data scientist
- business analyst
- domain-specific manager
- computer systems analyst
- data mining analyst
- business intelligence specialist
Industrial Collaboration
Prepare for your next role and gain valuable hands-on field experience during your capstone project. Previous students have conducted projects including:
- Understanding Chronic Conditions, Healthcare Accessm and Mental Health through Data Science
- Analyzing the Impact of S&P Stock Market Trends on the FHFA House Price Index
- Atlantic Sturgeon Habitat Suitability Analysis in the Chesapeake Bay
- Predicting Corporate Performance using Interrupted Time Series Analysis