- 1.Data Science professionals earn a median salary of $108,020/year, with 35% job growth projected through 2032—much faster than average.
- 2.Our top-ranked data science programs are University of Michigan-Ann Arbor, Columbia University in the City of New York, and University of Wisconsin-Madison—selected based on graduation rates, program size, and career outcomes.
- 3.Best value: University of Central Florida offers data science degrees at just $4,478/year with a 93% graduation rate.
- 4.188 accredited data science programs available nationwide, with options at every degree level from associate's to doctoral.
- 5.Entry-level positions typically require a bachelor's degree; master's degrees unlock senior roles with 20-40% higher salaries and leadership opportunities.
Source: BLS OEWS 2024
Best Data Science Programs - Top 10
These are the best data science programs in the United States based on our comprehensive methodology that considers graduation rates, program size, institutional reputation, and career outcomes. Rankings are updated annually using data from IPEDS and BLS.
Best Data Science Programs - Top 10
University of Michigan-Ann Arbor
Doctoral: Very High Research (R1)
Michigan's MS in Data Science is jointly owned and operated by four separate departments - CSE, Statistics, School of Information, and Biostatistics - creating an unusually comprehensive interdisciplinary curriculum that balances statistical theory with computational implementation across diverse data domains.
Program Overview
The University of Michigan-Ann Arbor's Master's in Data Science represents a unique collaborative effort between four powerhouse departments: Computer Science and Engineering (CSE), Statistics, School of Information, and Biostatistics. This interdisciplinary approach ensures students receive balanced training in both statistical rigor and computational prowess, combining the distinct educational strengths of each contributing department. Located in the Bob and Betty Beyster Building on U-M's engineering campus, the program sits within the Computer Science and Engineering Division, which is part of the highly-ranked Department of Electrical Engineering and Computer Science in the College of Engineering.
The program is specifically designed to produce graduates who understand data representation and analysis at an advanced level, with particular emphasis on working with large heterogeneous datasets in multi-computer environments. Students develop the ability to identify relevant datasets, apply appropriate statistical and computational tools to answer complex questions posed by individuals, organizations, or governmental agencies, and design and evaluate analytical procedures that can be efficiently implemented across distributed computing systems.
Degree Programs
Location Advantages
- •Part of highly-ranked College of Engineering
- •Access to resources from four collaborating departments
- •Located in Ann Arbor's technology corridor
Career Outcomes
Columbia University in the City of New York
Doctoral: Very High Research (R1)
Columbia's Data Science Institute houses one of the world's most comprehensive data science ecosystems, with 400+ affiliated faculty across eight specialized research centers and a 'Data for Good' mission that tackles society's toughest challenges while maintaining direct industry partnerships.
Program Overview
Columbia University's MS in Data Science stands as one of the most highly rated and sought-after advanced data science programs in the world, uniquely positioned within the prestigious Data Science Institute. This rigorous 3-semester program (plus summer internship/research) costs $60,000 in tuition and operates as a collaborative effort between three powerhouse departments: the Graduate School of Arts and Sciences' Department of Statistics, Columbia Engineering's Department of Computer Science, and the Department of Industrial Engineering and Operations Research. Students don't just study data science—they live it through original research opportunities, industry capstone projects with real partners, and direct interaction with world-class faculty who are actively shaping the field.
What sets Columbia's program apart is its 'Data for Good' philosophy, where students engage with eight specialized research centers tackling everything from smart cities and cybersecurity to health analytics and AI for sciences and engineering. The program combines academic rigor with practical application, offering seminars, industry events, and real-world exposure that gives students what current MS student Bavna Rajan calls 'the whole package—the academics and the industry exposure together.' With over 1,500 alumni now working at companies ranging from Google and Meta to Goldman Sachs and McKinsey, the program has established itself as a pipeline to leadership positions across all sectors.
Degree Programs
Research Labs & Institutes
Infrastructure, buildings, transportation, and urban environment optimization
Data-driven methods for individual and healthcare system improvement
Massive-scale computing systems for data processing and analysis
Data security and privacy throughout data lifecycle
Risk management and decision support tools using big data
Core research problems cutting across data sciences and engineering
Location Advantages
- •New York City's data science and tech ecosystem
- •Direct access to Wall Street financial firms
- •Proximity to major tech companies and startups
Career Outcomes
Alibaba, Amazon, Google, Meta, Microsoft
University of Wisconsin-Madison
Doctoral: Very High Research (R1)
UW-Madison operates one of the first online data science master's programs in the nation through its multi-campus collaboration, while its on-campus program uniquely bridges the Statistics and Computer Sciences departments with a curriculum addressing emerging areas of applied statistical and computing research.
Program Overview
The University of Wisconsin-Madison MS in Data Science represents a joint professional program between the Statistics and Computer Sciences departments, administered by the Statistics Department. This 30-credit program blends computational and statistical thinking to address data-rich problems across diverse fields. Students complete core coursework in statistics (STAT 611-613), computer sciences algorithms/systems/human-data interaction (9 credits), machine learning (6 credits), and flexible electives. The program offers both a traditional 1.5-2 year track and an accelerated pathway for qualified UW-Madison alumni that can be completed in just three semesters. With face-to-face instruction and accelerated options available, the program prepares graduates for roles as data analysts and data scientists or further education in quantitative fields.
Notably, UW-Madison also partners with Wisconsin Online Collaboratives to offer a separate 100% online Master of Science in Data Science through UW-Eau Claire, UW-Green Bay, UW-La Crosse, UW-Oshkosh, UW-Stevens Point, and UW-Superior. This online program was one of the first online data science programs in the nation and features asynchronous learning with hands-on skills in Python, machine learning, and cloud computing.
Degree Programs
Research Labs & Institutes
Powered by American Family Insurance, advancing research through data science with $20M in research grants
Location Advantages
- •Wisconsin tech corridor
- •Strong connections to agricultural and healthcare sectors
- •Access to American Family Insurance and other major Wisconsin employers
Industry Partners
Career Outcomes
Medical College of Wisconsin, Various healthcare, finance, and tech companies
Certifications & Designations
Admissions
University of Southern California
Doctoral: Very High Research (R1)
USC houses the Information Sciences Institute (ISI), a world-renowned research center that pioneered ARPAnet technologies and continues to lead breakthroughs in AI and data science, while the program's unique 'lived in the data' philosophy ensures students graduate with real-world experience through extensive hands-on projects and professional practicums.
George Mason University
Doctoral: Very High Research (R1)
George Mason's Department of Computational and Data Sciences is globally recognized as one of only a few departments offering comprehensive data science education at all degree levels, while the Data Analytics Engineering program offers an exceptional 14 specialized concentrations including unique tracks like Naval Engineering and Cyber Analytics.
Virginia Polytechnic Institute and State University
Doctoral: Very High Research (R1)
Virginia Tech's Data Science program uniquely offers three flexible pathways including an accelerated option for undergraduates and a part-time Northern Virginia hybrid program, while emphasizing interdisciplinary training that combines data science with domain expertise across fields from environmental conservation to biomedical research.
University of Virginia-Main Campus
Doctoral: Very High Research (R1)
UVA operates one of the few dedicated Schools of Data Science in the nation, built with a transformative $120 million founding gift and designed as a 'school without walls' that emphasizes responsible data science for the common good rather than purely technical applications.
Pennsylvania State University-Main Campus
Doctoral: Very High Research (R1)
Penn State's intercollege Data Sciences program uniquely allows students to specialize in Applied, Computational, or Statistical Modeling tracks while reuniting for shared capstone experiences, creating graduates who understand data science's multiple dimensions. The university's R1 research status combined with specialized labs like the $1 billion research engine creates unprecedented opportunities for undergraduates to engage in advanced research.
University of Illinois Urbana-Champaign
Doctoral: Very High Research (R1)
Illinois created one of the first fully online Master of Computer Science in Data Science programs with courses taught by faculty who have produced seminal research in data sciences, while offering unprecedented flexibility through cross-school collaboration between Statistics, Computer Science, and Information Sciences.
University of Pennsylvania
Doctoral: Very High Research (R1)
Penn's MSE in Data Science stands out for its unique depth area specialization system, allowing students to apply data science techniques across diverse fields from digital humanities to public policy, all while being housed in the newly opened Amy Gutmann Hall—the dedicated hub for data science innovation backed by a $60 million IDEAS initiative.
Our rankings methodology weighs program strength (25%), graduation rate (20%), career outcomes (15%), institutional quality (12%), industry recognition (10%), selectivity (10%), and data transparency (8%). Learn more about our methodology →
What is Data Science?
Data science is an interdisciplinary field that combines statistical analysis, machine learning, programming, and domain expertise to extract actionable insights from large, complex datasets. Unlike traditional computer science (which focuses on computation and systems) or pure statistics, data science emphasizes solving real-world business problems through data-driven decision making.
A data science degree covers programming (Python, R, SQL), statistics and probability, machine learning algorithms, data visualization, big data tools (Hadoop, Spark), databases, and domain-specific applications in business, healthcare, finance, or other industries. The field sits at the intersection of mathematics, computer science, and subject matter expertise.
Data scientists work across virtually every industry: tech companies (Google, Netflix, Meta), finance (banks, hedge funds), healthcare (pharmaceuticals, hospitals), retail (e-commerce, supply chain), government (policy analysis, public health), and consulting firms. The role involves collecting data, cleaning and preparing datasets, building predictive models, and communicating insights to stakeholders.
Who Should Study Data Science?
Data science is ideal for students who enjoy working with numbers, solving complex problems, and uncovering patterns in data. Strong mathematical foundations are essential, particularly in statistics and linear algebra. You should be comfortable with programming and curious about how data can drive business decisions.
- Analytical thinkers who enjoy finding patterns and insights in complex information
- Math-strong students comfortable with statistics, probability, and linear algebra
- Problem solvers interested in using data to answer business questions
- Communication-oriented individuals who can translate technical findings for non-technical audiences
- Curious learners excited about machine learning and artificial intelligence applications
Data science differs from pure computer science by focusing more on analysis and insights rather than building systems. It requires stronger statistical knowledge than typical CS programs but less systems programming. If you enjoy research, experimentation, and working with stakeholders to solve business problems, data science may be ideal.
Data Science Degree Levels Compared
Data science programs are available at multiple levels, though master's degrees are most common as the field emerged from graduate-level interdisciplinary programs
Data Science Programs by Degree Level
2-year programs for career entry or transfer to bachelor's programs
Top-ranked undergraduate programs nationwide
Top graduate programs for specialization and advancement
PhD programs for research and academic careers
Flexible online programs for working professionals
Best Data Science Programs - Bachelor's
A bachelor's degree in data science is the standard credential for entry-level positions. These 4-year programs provide comprehensive training and hands-on experience.
Best Data Science Programs - Top 3 Bachelor's
University of Michigan-Ann Arbor
144 graduates, 92% grad rate, Score: 81.0
University of Wisconsin-Madison
323 graduates, 83% grad rate, Score: 78.0
Virginia Polytechnic Institute and State University
173 graduates, 95% grad rate, Score: 74.6
4. Pennsylvania State University-Main Campus (University Park, PA) - Score: 71.1, Tuition: $19,672
5. Northeastern University (Boston, MA) - Score: 66.7, Tuition: $62,000
6. Northwestern University (Evanston, IL) - Score: 66.6, Tuition: $64,887
7. Columbia University in the City of New York (New York, NY) - Score: 66.4, Tuition: $64,526
8. William & Mary (Williamsburg, VA) - Score: 65.9, Tuition: $18,253
9. Smith College (Northampton, MA) - Score: 65.5, Tuition: $61,260
10. Worcester Polytechnic Institute (Worcester, MA) - Score: 61.1, Tuition: $57,960
Best Data Science Programs - Master's
A master's degree in data science prepares students for senior and specialized roles. These 1-2 year programs offer advanced expertise and leadership training.
Best Data Science Programs - Top 3 Master's
Columbia University in the City of New York
240 graduates, 100% grad rate, Score: 80.3
University of Southern California
74 graduates, 92% grad rate, Score: 77.1
George Mason University
319 graduates, 80% grad rate, Score: 75.1
4. University of Virginia-Main Campus (Charlottesville, VA) - Score: 74.4, Tuition: $18,823
5. University of Michigan-Ann Arbor (Ann Arbor, MI) - Score: 72.3, Tuition: $17,977
6. University of Illinois Urbana-Champaign (Champaign, IL) - Score: 70.0, Tuition: $14,768
7. University of Pennsylvania (Philadelphia, PA) - Score: 69.5, Tuition: $58,620
8. Northeastern University (Boston, MA) - Score: 69.4, Tuition: $62,000
9. The University of Texas at Austin (Austin, TX) - Score: 67.0, Tuition: $11,678
10. Rice University (Houston, TX) - Score: 67.0, Tuition: $57,210
Best Data Science Programs - Online
Online data science programs offer flexibility for working professionals. Top accredited programs provide the same curriculum quality as on-campus alternatives.
Best Data Science Programs - Top 3 Online
University of Michigan-Ann Arbor
144 graduates, 92% grad rate, Score: 81.0
University of Wisconsin-Madison
323 graduates, 83% grad rate, Score: 78.0
University of Southern California
74 graduates, 92% grad rate, Score: 77.1
4. George Mason University (Fairfax, VA) - Score: 75.1, Tuition: $10,095
5. University of Illinois Urbana-Champaign (Champaign, IL) - Score: 75.0, Tuition: $14,768
6. Virginia Polytechnic Institute and State University (Blacksburg, VA) - Score: 74.6, Tuition: $12,698
7. University of Virginia-Main Campus (Charlottesville, VA) - Score: 74.4, Tuition: $18,823
8. Pennsylvania State University-Main Campus (University Park, PA) - Score: 71.1, Tuition: $19,672
9. University of Pennsylvania (Philadelphia, PA) - Score: 69.5, Tuition: $58,620
10. The University of Texas at Austin (Austin, TX) - Score: 67.0, Tuition: $11,678
Best Data Science Programs - Associate's
An associate's degree in data science provides a 2-year pathway into the field. These programs are ideal for career starters or those planning to transfer to a 4-year program.
Best Data Science Programs - Top 3 Associate's
Pierce College District
7 graduates, 93% grad rate, Score: 52.3
Santa Monica College
1 graduates, 95% grad rate, Score: 48.7
Florida State College at Jacksonville
4 graduates, 89% grad rate, Score: 47.5
4. College of Southern Nevada (Las Vegas, NV) - Score: 41.8, Tuition: $3,465
5. Miami Dade College (Miami, FL) - Score: 41.0, Tuition: $1,987
6. Remington College-Online Dallas (Dallas, TX) - Score: 39.3, Tuition: $15,764
7. St Petersburg College (St. Petersburg, FL) - Score: 39.3, Tuition: $1,943
8. De Anza College (Cupertino, CA) - Score: 38.8, Tuition: $1,395
9. Gateway Technical College (Kenosha, WI) - Score: 38.4, Tuition: $4,386
10. Georgia Piedmont Technical College (Clarkston, GA) - Score: 36.3, Tuition: $2,400
Best Data Science Programs - Graduate
Graduate programs in data science (PhD and doctoral degrees) prepare students for research, academic, and senior leadership positions.
Best Data Science Programs - Top 3 Graduate
University of California-Berkeley
52 graduates, 96% grad rate, Score: 96.5
Carnegie Mellon University
34 graduates, 98% grad rate, Score: 91.3
Massachusetts Institute of Technology
68 graduates, N/A% grad rate, Score: 88.4
4. University of Southern California (Los Angeles, CA) - Score: 85.7, Tuition: $66,640
5. University of Illinois Urbana-Champaign (Champaign, IL) - Score: 85.6, Tuition: $14,768
6. Stanford University (Stanford, CA) - Score: 84.6, Tuition: $61,731
7. Cornell University (Ithaca, NY) - Score: 83.4, Tuition: $65,204
8. Princeton University (Princeton, NJ) - Score: 82.6, Tuition: $59,710
9. Purdue University-Main Campus (West Lafayette, IN) - Score: 81.6, Tuition: $9,718
10. University of Washington-Seattle Campus (Seattle, WA) - Score: 80.8, Tuition: $11,524
Most Affordable Data Science Programs
Looking for quality data science education without the hefty price tag? These programs offer the best value—balancing tuition costs with strong academic outcomes and career prospects. Our Value Score factors in graduation rates, program strength, and institutional quality relative to cost.
Top 5 Most Affordable Data Science Programs
| Rank | Institution | Location | Tuition | Value Score | Grad Rate |
|---|---|---|---|---|---|
| 1 | University of Central Florida | Orlando, FL | $4,478 | 122.0 | 93% |
| 2 | Bellevue College | Bellevue, WA | $4,074 | 115.0 | 96% |
| 3 | Florida State University | Tallahassee, FL | $4,640 | 108.8 | — |
| 4 | University of West Florida | Pensacola, FL | $3,735 | 108.6 | 84% |
| 5 | University of North Carolina Wilmington | Wilmington, NC | $4,443 | 103.8 | 79% |
Data Science Career Outcomes
Data science graduates enter one of the fastest-growing and highest-paying career fields. The BLS projects 35% job growth for data scientists through 2032—much faster than average for all occupations. For detailed compensation analysis, see our data scientist salary guide.
Career Paths
Data Scientist
SOC 15-2051Analyze complex data using statistical methods and machine learning to extract actionable business insights.
AI/ML Engineer
SOC 15-2051Design and implement machine learning systems and artificial intelligence applications.
Data Analyst
SOC 15-2041Collect, process, and perform statistical analysis on large datasets to support business decisions.
Business Intelligence Analyst
SOC 15-2041Transform business data into actionable insights through reporting, dashboards, and analysis.
Research Scientist
SOC 19-1041Conduct advanced research using data science methods in academic, government, or industry settings.
Quantitative Analyst
SOC 15-2041Apply mathematical and statistical methods to financial and risk management problems.
Data Science Curriculum Overview
Data science programs combine computer science, statistics, and domain expertise. Core curricula typically include programming, statistical analysis, machine learning, data visualization, and practical applications across various industries.
- Programming: Python, R, SQL for data manipulation and analysis
- Mathematics: Statistics, probability, linear algebra, calculus (varies by program)
- Machine Learning: Supervised and unsupervised learning, neural networks, deep learning
- Data Engineering: Database design, big data tools (Hadoop, Spark), cloud platforms
- Visualization: Tableau, D3.js, matplotlib for communicating insights
- Domain Applications: Business analytics, bioinformatics, finance, marketing, etc.
Many programs emphasize hands-on projects, internships, and capstone experiences working with real datasets. For detailed curriculum breakdown, see our data science curriculum guide.
Data Science Programs by State
Arizona
California
Colorado
Connecticut
Florida
Georgia
Illinois
Indiana
Maryland
Massachusetts
Michigan
Minnesota
Missouri
New Jersey
New York
North Carolina
Ohio
Oregon
Pennsylvania
Tennessee
Texas
Utah
Virginia
Washington
Wisconsin
Data Science vs Related Fields
Data science sits at the intersection of statistics, programming, and domain expertise. Unlike software engineering (building products) or CS (understanding computation), data science focuses on extracting insights and making predictions from data.
The statistical foundation is what distinguishes data scientists from software developers who use ML libraries. Understanding probability distributions, hypothesis testing, experimental design, and statistical inference helps you avoid the many pitfalls of drawing false conclusions from data.
Data science roles vary dramatically by industry. A data scientist at a tech company might build recommendation systems, while one in healthcare analyzes clinical trial data, and one in finance builds trading models. Domain expertise often matters as much as technical skills for senior roles.
Which Should You Choose?
- You want to focus specifically on extracting insights from data
- You enjoy statistics, machine learning, and predictive modeling
- You want to work across multiple industries and domains
- You're interested in business impact and decision-making support
- You want broad foundations in computing and systems
- You're interested in software development beyond just data analysis
- You prefer building applications and systems over analyzing data
- You want maximum career flexibility in tech
- You're specifically interested in machine learning and AI systems
- You want to focus on algorithm development and research
- You're interested in cutting-edge AI applications
- You prefer deeper technical focus over business applications
- You prefer theoretical mathematical foundations
- You're interested in research methodology and experimental design
- You want strong preparation for academic or research careers
- You're less interested in programming and more in statistical theory
Is a Data Science Degree Worth It?
For most students interested in analytics, yes. The combination of high starting salaries ($68,000+ for new grads), exceptional job growth (35% through 2032), industry versatility, and strong demand makes data science one of the most promising degree choices available.
When it's worth it: You're genuinely interested in data analysis and statistical thinking, comfortable with programming and mathematics, and excited about solving business problems through data. The degree provides structured learning, networking opportunities, and credibility that bootcamps alone often can't provide.
When to consider alternatives: You already have strong programming skills and just need specific data science tools (data science bootcamps may be faster), you're working in a related field and need targeted upskilling, or you have significant financial constraints.
The field is still evolving rapidly, with new applications emerging in healthcare, sustainability, and emerging technologies. Early investment in a comprehensive data science education positions you for long-term career growth.
Alternative Paths to Data Science Careers
While a data science degree is increasingly the standard path, alternatives exist for those with different backgrounds, timelines, or specific goals
- Best Data Science Bootcamps — Intensive 12-24 week programs for career switchers
- Best Data Analytics Bootcamps — Shorter programs focused on business analytics
- AWS Certifications Roadmap — Cloud credentials for data engineering roles
- Data Analytics Certification Guide — Industry certifications for skill validation
- Bootcamp vs Master's Degree — ROI analysis for career changers
Many professionals combine approaches—starting with online courses or bootcamps to test interest, then pursuing a formal degree for advancement. Statistics, mathematics, or computer science backgrounds often provide good foundations for transitioning to data science.
Data Science Degree FAQ
Based on 485 programs from IPEDS 2023, BLS OES 2024, NSA CAE Database
Number of data science graduates from IPEDS 2023, indicating program resources and faculty depth
6-year completion rate from IPEDS 2023, measuring student success
State-level salary data from BLS OES 2024 for relevant occupations
Carnegie Classification with bonus for R1 research universities
NSA/DHS CAE-CD designation for cybersecurity programs, ABET accreditation for engineering
Admission rate from IPEDS 2023 (lower = more selective)
Completeness of reported metrics to IPEDS
Related Resources
Taylor Rupe
Full-Stack Developer (B.S. Computer Science, B.A. Psychology)
Taylor combines formal training in computer science with a background in human behavior to evaluate complex search, AI, and data-driven topics. His technical review ensures each article reflects current best practices in semantic search, AI systems, and web technology.