Your guide to data science graduate programs

The program cards/tables featured on this page were last updated in October 2026. For the most current program information, please refer to the official website of the respective school.

What is data science?

Data science is a dynamic field that merges math, computer science, and statistics to analyze and draw insights from datasets. From capturing data to communicating results, data scientists play an important role in helping businesses make strategic decisions and optimize outcomes.

According to the U.S. Department of Labor’s O*NET profile for data scientists, updated in 2026, the work involves applying data mining, data modeling, natural language processing, and machine learning to large structured and unstructured datasets, then visualizing, interpreting, and reporting the findings.

In the business world, data science can help corporations understand consumer and market trends. Data science can also be used to collect and analyze information in other industries, with different end goals. For example:

• Gathering census data for public policy professionals to predict election outcomes or identify marginalized groups.
• Analyzing biostatistics and disease rates to inform medical solutions and health recommendations.
• Exploring student outcomes and identifying early interventions to prevent dropouts.

Master’s in data science programs and related degrees

From machine learning and artificial intelligence to data systems administration and security, there are a variety of focus areas and types of programs you can pursue through higher education. Some of your options include master’s degrees in data science, bachelor’s degrees in data science, bootcamps, and short courses.

Master’s in data science

A master’s in data science is a graduate-level program in the field. The National Center for Education Statistics’ program classification describes a general data science program as one that focuses on analyzing large-scale data sources from the perspectives of applied statistics, computer science, data storage, data representation, data modeling, and mathematics. Individual programs set their own curricula, but the classification includes instruction in areas such as:

• Statistics and quantitative analysis
• Data management and data mining
• Computer programming and algorithms
• Mathematical modeling and visual analytics

To build programming skills before or alongside a degree, explore our guides to Python, R, and SQL.

Master’s in business analytics

Business analytics uses data science to understand and predict consumer, market, and world economic trends. A master’s in business analytics is a graduate-level program in this area, and NCES describes business analytics programs as preparing individuals to apply data science to solve business challenges. The classification lists instruction in areas such as:

• Machine learning and optimization methods
• Computer algorithms, probability, and stochastic models
• Strategy, consumer behavior, and marketing
• Visual analytics

For business analytics enthusiasts, “data-driven decisions” is the name of the game.

Master’s in information systems

To architect new technologies for companies, you’ll need to be well versed in using information systems and operations. A master’s degree in information systems is a graduate-level program in this area. The NCES classification describes management information systems programs as generally preparing individuals to provide and manage data systems and related facilities for processing and retrieving internal business information. It lists instruction in areas such as:

• Data storage and security
• Business systems networking
• Management information systems policy and planning

Other related master’s degrees in data science

Computer science, computer engineering, and cybersecurity are related fields, and each is associated with its own occupations. The occupation titles below come from O*NET, which describes what workers in each occupation do. These are examples, not guaranteed outcomes of any degree, and employers set their own education requirements.

Computer science occupations

• Computer and information research scientists
• Computer systems analysts
• Computer science teachers, postsecondary
• Information technology project managers
• Computer and information systems managers

Learn more about an online master’s in computer science to jump-start your career.

Computer engineering occupations

• Computer hardware engineers
• Computer network architects
• Software developers

Explore starting your career in computer engineering with a master’s online.

Cybersecurity occupations

• Information security analysts
• Information security engineers
• Digital forensics analysts

Discover online master’s in cybersecurity programs to kick off your career.

If you want to apply data science within a specific field, such as healthcare, earth sciences, or public policy, you can also explore these related specializations:

Bootcamps

Bootcamps are short, skills-focused training programs, and providers vary in topics, schedules, and formats. If you are considering one to build or update technical skills in areas like data science, analytics, cybersecurity, or coding, review each provider’s published curriculum, schedule, and costs before you enroll.

Technology bootcamps differ widely, so when you compare them, look at:

• What the curriculum covers and how much prior experience it assumes.
• Whether classes are in person, online, or both, and how the schedule fits around other obligations, like a full-time job.
• What career support the provider describes, and whether it publishes outcomes data you can check.
• Who offers the program, and which accreditation or approval, if any, applies to it.

Short courses

Online short courses let you study a single topic without committing to a full degree program. Length, format, and credentials vary by provider, so check how each course is structured before you enroll.

When you compare data science short courses, look at:

• The topics and tools the syllabus covers.
• The time commitment the provider lists, and whether the course is self-paced or follows a set schedule.
• Whether the course carries college credit or is noncredit.
• Whether you earn a certificate of completion for a single course or a certificate for a sequence of courses.

Even if you’re not looking to change careers, you can take a short course to explore a topic before committing to a longer program.

Choosing the best MS in data science program for you

Online vs. on-campus data science programs

Online and on-campus data science master’s programs can differ in how often classes meet live, whether coursework is asynchronous, whether any campus visits are required, and what networking and career support each program offers. Compare those details for each program you consider.

When searching for the right program for you, research its overall academic quality and credibility to determine if it will suit your needs, learning style, and career goals.

Full- vs. part-time data science programs

Part-time data science degree programs may appeal to students with limited time. Programs differ in whether you can enroll full time, part time, or both, and whether classes are held in person or online.

Determine how much time you have to commit to a program and how soon you wish to enter the field. If you are looking to become a data scientist sooner rather than later, pursuing a full-time program means you’ll earn your degree in a shorter amount of time. Employers set their own requirements for each role, so review current job postings for the roles you want to see which credentials and experience they ask for.

When you compare programs, ask how long full-time and part-time students typically take to finish, how many credits are required, and whether required courses are offered every term.

How to check a program’s credibility

Before you apply, check whether the school holds institutional accreditation and whether any separate programmatic accreditation applies to the program.

• Institutional accreditation: The U.S. Department of Education does not accredit institutions or programs, but the Secretary of Education recognizes accrediting agencies as reliable authorities on the quality of the education they accredit. The Department’s accreditation database lists accredited postsecondary institutions and programs that you can search.
• Programmatic accreditation: Programmatic accreditation applies to a specific program rather than to a whole school. Academic accreditation in the United States is voluntary, and ABET accredits programs only, not institutions. ABET publishes data science accreditation criteria that cover five areas, including the core data science lifecycle, advanced coursework, and a major integrating project. Because ABET treats data science as a new and developing program area, and its page highlights the bachelor’s level in particular, a master’s program without ABET accreditation is not by itself a warning sign. Ask each school which programmatic accreditations, if any, apply to the program you are considering.

To compare programs by location, browse our state-by-state directory.

Frequently asked questions

Do you need a master’s degree to work as a data scientist?

Not necessarily. O*NET places data scientists in Job Zone Four, where it says most occupations require a four-year bachelor’s degree, but some do not. Employers set their own requirements, so check job postings for the education they ask for.

Does a data scientist need a license?

O*NET’s data scientist profile lists no license requirement. Employers set their own expectations, so check job postings for the credentials or certifications they ask for.

Is a master’s in data science STEM-designated?

The Department of Homeland Security’s STEM list, last updated July 22, 2024, includes CIP code 30.7001, Data Science, General. A listed code is only one condition for the 24-month STEM OPT extension. Under the federal regulation, the student must also be in a valid period of post-completion OPT, the degree must come from a U.S. institution accredited by an agency the Department of Education recognizes, the employer must be enrolled in E-Verify, and the student and employer must complete a training plan (Form I-983) before the school’s designated school official (DSO) recommends the extension. Whether a specific program qualifies depends on the CIP code the school assigns to it, so ask the school’s DSO about the program and your own eligibility.

Where can I find funding for a data science master’s degree?

Start with the financial aid office at each school you are considering, then explore our list of data science scholarships.