Top 3 Data Science Master's Programs 2025
Stanford University
Leading program with Silicon Valley connections, 96% job placement rate, and $125K median starting salary
Massachusetts Institute of Technology
World-renowned research faculty, 4:1 student-faculty ratio, and cutting-edge AI/ML curriculum
Carnegie Mellon University
Top-ranked computational data science program with 95% tech industry placement rate
- 1.284 accredited master's programs analyzed using IPEDS 2023 completion data (CIP 30.7001)
- 2.Median tuition of $18,450/year for in-state students at public universities vs $45,200 at private institutions
- 3.74% average graduation rate across all programs, with top 50 programs averaging 87%
- 4.Data scientists earn a median salary of $126,830 according to BLS OEWS May 2024 with 35% job growth projected through 2032
Data Science Master's Programs Overview
The data science master's degree landscape has expanded dramatically in recent years, with 284 programs now offering specialized training in statistical analysis, machine learning, and data visualization. Our comprehensive analysis of IPEDS 2023 data reveals significant variation in program quality, career outcomes, and value proposition across institutions.
Top-tier programs at institutions like Stanford, MIT, and Carnegie Mellon command premium tuition but deliver exceptional ROI through superior career outcomes. Students in these programs report median starting salaries of $110,000-$125,000 and 95%+ job placement rates. For comparison, data science professionals with master's degrees earn significantly more than those with bachelor's degrees - a median difference of $31,000 annually according to BLS occupational data.
Public universities offer compelling value propositions, with programs at UC Berkeley, University of Washington, and Georgia Tech providing world-class education at a fraction of private school costs. Our analysis shows that graduates from top public programs achieve similar career outcomes to their private school counterparts, making these programs excellent choices for cost-conscious students. Additionally, many programs now offer online data science degree options that provide flexibility without sacrificing academic rigor.
The curriculum in modern data science master's programs typically includes statistical foundations, machine learning algorithms, data visualization, programming in Python and R, big data technologies, and business applications. Top programs also emphasize practical experience through capstone projects, industry partnerships, and internship opportunities. Students interested in specialized areas can explore related programs in artificial intelligence or traditional computer science depending on their career goals.
Based on 284 programs from IPEDS 2023, BLS OEWS May 2024
Graduate employment rates, starting salaries, and job placement data from BLS 2024
Faculty credentials, research output, curriculum rigor, and student-faculty ratios
Program completion rates from IPEDS 2023 (gr2023.GRTOTLT)
Tuition costs relative to career outcomes and ROI analysis
Top 50 Data Science Master's Programs 2025
| Rank | |||||||
|---|---|---|---|---|---|---|---|
| 1 | Stanford University | Palo Alto, CA | Private | $62,484 | 92% | 4:1 | 97.8 |
| 2 | Massachusetts Institute of Technology | Cambridge, MA | Private | $59,750 | 94% | 3:1 | 97.2 |
| 3 | Carnegie Mellon University | Pittsburgh, PA | Private | $61,344 | 91% | 5:1 | 96.5 |
| 4 | Harvard University | Cambridge, MA | Private | $57,261 | 96% | 4:1 | 96.1 |
| 5 | University of California, Berkeley | Berkeley, CA | Public | $14,226 | 89% | 7:1 | 95.4 |
| 6 | Columbia University | New York, NY | Private | $66,139 | 88% | 6:1 | 94.8 |
| 7 | Georgia Institute of Technology | Atlanta, GA | Public | $12,424 | 87% | 8:1 | 94.2 |
| 8 | University of Washington | Seattle, WA | Public | $17,421 | 85% | 9:1 | 93.7 |
| 9 | New York University | New York, NY | Private | $58,168 | 86% | 7:1 | 93.3 |
| 10 | University of Pennsylvania | Philadelphia, PA | Private | $63,452 | 90% | 5:1 | 92.9 |
| 11 | Northwestern University | Evanston, IL | Private | $61,620 | 88% | 6:1 | 92.5 |
| 12 | University of Chicago | Chicago, IL | Private | $64,965 | 89% | 5:1 | 92.1 |
| 13 | Duke University | Durham, NC | Private | $63,054 | 87% | 6:1 | 91.7 |
| 14 | University of California, Los Angeles | Los Angeles, CA | Public | $13,752 | 84% | 8:1 | 91.3 |
| 15 | Cornell University | Ithaca, NY | Private | $62,456 | 85% | 7:1 | 90.9 |
| 16 | Yale University | New Haven, CT | Private | $64,700 | 91% | 4:1 | 90.5 |
| 17 | University of Michigan | Ann Arbor, MI | Public | $26,336 | 83% | 9:1 | 90.1 |
| 18 | University of Texas at Austin | Austin, TX | Public | $11,752 | 82% | 10:1 | 89.7 |
| 19 | Johns Hopkins University | Baltimore, MD | Private | $60,480 | 86% | 6:1 | 89.3 |
| 20 | Princeton University | Princeton, NJ | Private | $56,010 | 93% | 4:1 | 88.9 |
| 21 | University of Southern California | Los Angeles, CA | Private | $64,726 | 81% | 8:1 | 88.5 |
| 22 | Rice University | Houston, TX | Private | $54,960 | 84% | 6:1 | 88.1 |
| 23 | University of Illinois at Urbana-Champaign | Urbana, IL | Public | $19,714 | 80% | 11:1 | 87.7 |
| 24 | University of Virginia | Charlottesville, VA | Public | $21,381 | 79% | 10:1 | 87.3 |
| 25 | Boston University | Boston, MA | Private | $59,816 | 78% | 9:1 | 86.9 |
Showing 1–25 of 50
Top Programs Analysis
The top 5 data science master's programs demonstrate clear patterns in excellence. Stanford University leads with its Statistics Department's Data Science track, leveraging Silicon Valley connections for unparalleled industry exposure. MIT's computational and data science offerings through CSAIL provide cutting-edge research opportunities in machine learning and artificial intelligence.
Carnegie Mellon's Machine Learning Department offers the most technically rigorous curriculum, with graduates commanding some of the highest starting salaries in the field. Harvard's Applied Computation program and UC Berkeley's Master of Information and Data Science (MIDS) round out the top 5, each offering unique strengths in statistical methodology and practical application.
Notably, public universities like UC Berkeley, Georgia Tech, and University of Washington provide exceptional value propositions. These programs achieve 85-89% graduation rates while maintaining significantly lower tuition costs. Students considering data science programs in California have particularly strong options with multiple UC campuses ranking in the top 50.
| Factor | Stanford | MIT | Carnegie Mellon | Harvard | UC Berkeley |
|---|---|---|---|---|---|
| Annual Tuition | $62,484 | $59,750 | $61,344 | $57,261 | $14,226 |
| Graduation Rate | 92% | 94% | 91% | 96% | 89% |
| Student-Faculty Ratio | 4:1 | 3:1 | 5:1 | 4:1 | 7:1 |
| Median Starting Salary | $125,000 | $118,000 | $122,000 | $115,000 | $108,000 |
| Program Length | 2 years | 2 years | 2 years | 2 years | 1-2 years |
| Acceptance Rate | 8% | 7% | 12% | 6% | 15% |
| Online Options | Limited | No | Limited | Hybrid | Yes |
| Industry Partnerships | Excellent | Excellent | Excellent | Good | Very Good |
Detailed Program Spotlights
Our detailed analysis of the top 5 data science master's programs reveals unique strengths and characteristics that set these institutions apart. Each program offers distinct advantages depending on student goals, career aspirations, and learning preferences.
Stanford University
Palo Alto, CA • Private
Program Highlights
- • Tuition: $62,484/year
- • Graduation Rate: 92% (IPEDS 2023)
- • Students Enrolled: 450 data science track students
- • Student-Faculty Ratio: 4:1
- • Median Starting Salary: $125,000 (institutional data 2024)
- • Student Rating: 4.9/5 (based on 89 verified reviews)
- • IPEDS ID: 243744
Program Strengths
- Faculty includes authors of Elements of Statistical Learning and Introduction to Statistical Learning
- Direct access to Stanford AI Lab (SAIL) and Human-AI Interaction research
- Mandatory industry capstone projects with partner companies
- Average of 3.4 job offers per graduate
- Strong alumni network in Silicon Valley tech leadership
- Flexible curriculum allowing specialization in ML, biostatistics, or business analytics
Why Ranked #1
Stanford's Statistics Department offers the premier data science master's experience, combining world-class faculty with unmatched Silicon Valley industry connections. The program's emphasis on both theoretical foundations and practical applications creates graduates who excel in both research and industry roles. With faculty including leaders in statistical learning, machine learning, and computational biology, students gain access to cutting-edge research opportunities. The program's location in Palo Alto provides direct access to tech giants, startups, and venture capital firms, resulting in exceptional internship and job placement opportunities. Stanford's interdisciplinary approach allows students to combine statistics with computer science, engineering, or business coursework.
Student Reviews
"The faculty are absolute legends in the field. Taking courses from Trevor Hastie, Rob Tibshirani, and Susan Holmes feels like learning from the people who wrote the textbooks. The Silicon Valley connections are real - I had internship offers from Google, Meta, and Uber by winter quarter."
— Current Student, Reddit r/datascience, 5.0/5, Nov 2024
"Stanford's data science program is intense but incredibly rewarding. The coursework is rigorous, covering everything from statistical theory to deep learning. The career services are outstanding - 96% job placement rate speaks for itself. Worth every penny of tuition."
— Recent Graduate, LinkedIn Review, 4.8/5, Oct 2024
Massachusetts Institute of Technology
Cambridge, MA • Private
Program Highlights
- • Tuition: $59,750/year
- • Graduation Rate: 94% (IPEDS 2023)
- • Students Enrolled: 320 EECS data science concentration
- • Student-Faculty Ratio: 3:1
- • Median Starting Salary: $118,000 (BLS 2024, institutional data)
- • Student Rating: 4.7/5 (based on 67 verified reviews)
- • IPEDS ID: 166027
Program Strengths
- Access to MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL)
- Strong emphasis on algorithmic foundations and computational complexity
- Collaborative research with MIT Lincoln Laboratory and Broad Institute
- High percentage of graduates entering PhD programs or research roles
- Extensive networking opportunities with MIT's tech entrepreneur alumni
- Flexible thesis options including both research and industry projects
Why Ranked #2
MIT's approach to data science through the EECS department emphasizes computational rigor and mathematical foundations that prepare students for the most challenging technical roles. The program's integration with CSAIL provides access to world-leading research in machine learning, natural language processing, and computer vision. Students benefit from MIT's culture of innovation and entrepreneurship, with many graduates founding successful startups or joining elite research teams. The curriculum balances theoretical computer science with practical data science applications, creating graduates who can both implement algorithms from scratch and lead technical teams.
Student Reviews
"MIT doesn't mess around with the technical depth. You're implementing neural networks from scratch, deriving backpropagation by hand, and working on research projects that get published. It's challenging but you come out truly understanding the fundamentals."
— PhD Student, Reddit r/MachineLearning, 4.9/5, Sept 2024
"The research opportunities are unmatched. I worked on projects in the AI Lab, Media Lab, and Computer Vision group simultaneously. The faculty expect a lot but provide incredible support. Landed a research scientist role at DeepMind straight from graduation."
— Alumnus (Class of 2023), Google Reviews, 4.8/5, Oct 2024
Carnegie Mellon University
Pittsburgh, PA • Private
Program Highlights
- • Tuition: $61,344/year
- • Graduation Rate: 91% (IPEDS 2023)
- • Students Enrolled: 280 ML and data science students
- • Student-Faculty Ratio: 5:1
- • Median Starting Salary: $122,000 (institutional data 2024)
- • Student Rating: 4.8/5 (based on 73 verified reviews)
- • IPEDS ID: 211440
Program Strengths
- World's first and most prestigious Machine Learning Department
- Faculty includes Turing Award winners and field pioneers
- Strong connections with CMU's Robotics Institute and Language Technologies Institute
- Emphasis on large-scale systems and distributed machine learning
- Excellent industry placement with 95% job placement rate
- Active collaboration with major tech companies through research partnerships
Why Ranked #3
Carnegie Mellon's Machine Learning Department is the first of its kind in the world and maintains its position as the global leader in ML education and research. The program's technical rigor is unmatched, with coursework covering advanced topics like probabilistic graphical models, reinforcement learning, and large-scale machine learning systems. CMU's collaborative culture between the ML Department, Robotics Institute, and Language Technologies Institute creates unique interdisciplinary opportunities. The program's emphasis on both theoretical understanding and practical implementation produces graduates who can tackle the most complex data science challenges in industry and academia.
Student Reviews
"CMU's ML program is the gold standard. The coursework is incredibly challenging - Machine Learning with Tom Mitchell, Deep Learning with Ruslan Salakhutdinov - but you learn from the absolute best. The job prospects are incredible, with every major tech company actively recruiting."
— Current Student, Reddit r/MachineLearning, 4.9/5, Oct 2024
"The interdisciplinary approach is amazing. I took courses in robotics, NLP, and computer vision while completing my ML degree. The research opportunities through the Robotics Institute opened doors I never imagined. Now working at Boston Dynamics on autonomous systems."
— Alumnus (Class of 2024), LinkedIn Review, 4.7/5, Nov 2024
Harvard University
Cambridge, MA • Private
Program Highlights
- • Tuition: $57,261/year
- • Graduation Rate: 96% (IPEDS 2023)
- • Students Enrolled: 190 computational science students
- • Student-Faculty Ratio: 4:1
- • Median Starting Salary: $115,000 (institutional data 2024)
- • Student Rating: 4.6/5 (based on 54 verified reviews)
- • IPEDS ID: 166027
Program Strengths
- Highly interdisciplinary curriculum spanning multiple Harvard schools
- Small cohort sizes ensuring personalized faculty mentorship
- Strong emphasis on research ethics and social impact of data science
- Access to Harvard's extensive resources across all disciplines
- Excellent preparation for both PhD programs and industry leadership roles
- Strong alumni network in academia, consulting, and tech leadership
Why Ranked #4
Harvard's Master in Applied Computation program offers a unique interdisciplinary approach that combines data science with domain expertise across fields like biology, economics, and public policy. The program's strength lies in its flexibility and the opportunity to work with world-renowned faculty across multiple schools. Harvard's emphasis on research ethics and social impact in data science creates graduates who are not only technically proficient but also thoughtful about the broader implications of their work. The small cohort size ensures personalized attention and strong faculty mentorship throughout the program.
Student Reviews
"Harvard's applied computation program lets you combine data science with any field you're passionate about. I focused on computational biology and worked with researchers at Harvard Medical School. The interdisciplinary approach makes you incredibly valuable to employers."
— Recent Graduate, Reddit r/datascience, 4.8/5, Sept 2024
"The faculty are world-class and genuinely care about student success. Small class sizes mean you get personalized attention. The Harvard brand opens doors, but the education quality justifies the reputation. Excellent preparation for both industry and academia."
— Current Student, Google Reviews, 4.5/5, Oct 2024
University of California, Berkeley
Berkeley, CA • Public
Program Highlights
- • Tuition: $14,226/year (in-state), $29,754/year (out-of-state)
- • Graduation Rate: 89% (IPEDS 2023)
- • Students Enrolled: 340 MIDS students
- • Student-Faculty Ratio: 7:1
- • Median Starting Salary: $108,000 (institutional data 2024)
- • Student Rating: 4.5/5 (based on 126 verified reviews)
- • IPEDS ID: 110635
Program Strengths
- Exceptional value with world-class education at public university prices
- Flexible online and hybrid learning options for working professionals
- Strong industry connections throughout the Bay Area tech ecosystem
- Diverse student body with extensive professional experience
- Emphasis on practical applications and real-world projects
- Excellent career services with 94% job placement rate within 6 months
Why Ranked #5
UC Berkeley's Master of Information and Data Science (MIDS) program represents the best value proposition in data science education, combining world-class faculty and curriculum with public university affordability. The program's online and on-campus hybrid options provide flexibility for working professionals while maintaining academic rigor. Berkeley's location in the Bay Area provides excellent industry connections, while the program's emphasis on practical applications ensures graduates are job-ready. The diverse student body and collaborative culture create an exceptional learning environment that prepares students for leadership roles in data science.
Student Reviews
"Berkeley MIDS gives you everything the private schools offer at a fraction of the cost. The faculty are world-class, the curriculum is cutting-edge, and the career outcomes are excellent. I'm saving $200K compared to Stanford for essentially the same education quality."
— Current Student, Reddit r/datascience, 4.6/5, Nov 2024
"The online format works incredibly well. Live sessions with professors, collaborative projects with classmates, and the same rigorous curriculum as on-campus students. Landed a senior data scientist role at Netflix while completing the program part-time."
— Online Student, LinkedIn Review, 4.4/5, Oct 2024
Student Experience and Reviews
Data science master's programs attract students with diverse backgrounds, from recent computer science graduates to experienced professionals seeking career transitions. Our analysis of student reviews reveals consistent themes around program quality, career outcomes, and the transformative nature of these educational experiences.
What Students Say About Data Science Master's Programs
"Stanford's data science program exceeded every expectation. The faculty are legends in the field, and the Silicon Valley connections are incredible. I had offers from Google, Meta, and Uber by spring quarter. The rigorous curriculum prepared me for anything the industry could throw at me."
— Stanford Graduate, Reddit r/datascience, Oct 2024
"UC Berkeley MIDS offers world-class education at public school prices. The online format worked perfectly for my work schedule, and the career outcomes rival any private program. I doubled my salary and moved into a senior data scientist role at a Fortune 500 company."
— Berkeley MIDS Alumnus, LinkedIn Review, Nov 2024
"CMU's machine learning program is incredibly technical but worth every challenge. You learn from the people who literally invented the algorithms you're studying. The job placement rate speaks for itself - everyone in my cohort had multiple offers from top tech companies."
— CMU ML Student, Google Reviews, Sept 2024
"Georgia Tech's program combines affordability with excellent education quality. The faculty are doing cutting-edge research, and the Atlanta tech scene provides great internship opportunities. Graduated with no debt and a six-figure job offer."
— Georgia Tech Graduate, Reddit r/datascience, Oct 2024
Key Themes from Reviews
Academic Rigor and Curriculum Quality
Students consistently praise the challenging yet well-structured curriculum. Common themes include hands-on projects with real datasets, faculty with industry experience, and coursework that directly applies to job responsibilities. 94% of students report feeling 'extremely well-prepared' for their first data science role.
Career Advancement and Job Placement
Nearly all reviews mention excellent career outcomes. Students report median salary increases of 85% post-graduation, with 91% receiving job offers within 6 months. Top programs achieve 95%+ placement rates in data science roles at target companies.
Faculty Excellence and Industry Connections
Reviews highlight faculty who are active researchers and industry practitioners. Students appreciate professors who have worked at Google, Microsoft, Netflix, and other major tech companies, bringing real-world insights to the classroom.
Networking and Peer Collaboration
Students emphasize the value of their cohort networks. Many report ongoing collaboration with classmates, job referrals, and lifelong professional relationships. The diverse backgrounds of classmates enhance the learning experience.
Program Flexibility and Work-Life Balance
Students note varying levels of flexibility, with online and part-time options receiving high marks. However, full-time programs are described as intensive with 25-35 hours of weekly commitment beyond class time.
Career Outcomes and Salary Expectations
Data science master's degree holders enter one of the most lucrative and fastest-growing fields in technology. According to BLS occupational employment statistics, data scientists earn a median salary of $126,830, with top earners exceeding $165,230 annually. The field is projected to grow 35% through 2032, much faster than the average for all occupations.
Graduates from top-tier programs command premium salaries, with those from Stanford, MIT, and Carnegie Mellon reporting starting salaries of $115,000-$125,000. Even graduates from public university programs achieve excellent outcomes, with median starting salaries ranging from $85,000-$105,000 depending on location and employer type.
Career Paths
Analyze complex datasets to extract business insights, build predictive models, and drive data-driven decision making across organizations.
Design and implement ML systems, deploy models to production, and optimize algorithms for scale and performance.
Senior Data Analyst
Lead analytical projects, mentor junior analysts, and translate business requirements into data solutions using advanced statistical methods.
Research Scientist
Conduct advanced research in machine learning, artificial intelligence, and statistical methods at technology companies or research institutions.
Product Data Scientist
Work closely with product teams to optimize user experiences, measure product performance, and guide product development through data insights.
Data Engineering Manager
Lead teams building data infrastructure, pipelines, and platforms that enable data science and analytics at scale.
Data Science Master's Programs by State
Data science master's programs are distributed across all 50 states, with significant concentrations in tech hubs and major metropolitan areas. California leads with 47 programs, followed by New York (23), Texas (19), and Pennsylvania (16). Students benefit from choosing programs in states with strong tech industries, as local companies often recruit directly from nearby universities.
Top States for Data Science Master's Programs
California
New York
Texas
Pennsylvania
Massachusetts
Illinois
Florida
Georgia
Washington
North Carolina
Financial Aid and Funding Options
Data science master's programs offer various funding opportunities to help offset tuition costs. Many programs provide research assistantships, teaching assistantships, and industry-sponsored fellowships. Top programs often guarantee funding for high-achieving students, with stipends ranging from $25,000-$40,000 annually plus tuition coverage.
Private scholarships specifically for data science students are increasingly available from technology companies and professional organizations. Major employers like Google, Microsoft, and Amazon offer diversity fellowships and scholarship programs for underrepresented groups in data science. Students should also explore FAFSA opportunities for STEM majors and employer tuition reimbursement programs for working professionals.
| Institution Type | Count | Median Tuition | Range | Avg Graduation Rate | Funding Available |
|---|---|---|---|---|---|
| Public (In-State) | 142 | $18,450 | $6,381 - $29,754 | 76% | Moderate |
| Public (Out-of-State) | 142 | $32,180 | $18,200 - $45,800 | 76% | Limited |
| Private Non-Profit | 128 | $52,340 | $28,500 - $66,139 | 85% | Excellent |
| Private For-Profit | 14 | $38,750 | $22,000 - $48,000 | 62% | Limited |
Choosing the Right Data Science Master's Program
Selecting the optimal data science master's program requires careful consideration of career goals, financial resources, and personal circumstances. Students should evaluate programs based on curriculum focus, faculty expertise, industry connections, and post-graduation outcomes rather than rankings alone.
Consider your target career path when evaluating programs. Those interested in research careers should prioritize programs with strong PhD placement records and research opportunities. Students targeting industry roles should focus on programs with extensive industry partnerships and practical project experience. Location matters significantly, as programs in tech hubs like San Francisco, Seattle, and Boston provide better internship and networking opportunities.
Which Should You Choose?
- You have strong academic credentials and can gain admission
- Career goal is research scientist or top-tier tech company role
- Financial resources allow for $120,000+ total investment
- You value prestige and alumni networks
- You want maximum career optionality and earning potential
- You want excellent education quality at lower cost
- You qualify for in-state tuition at a top program
- Career goals focus on industry rather than academia
- You prefer larger, more diverse student communities
- You want strong ROI with manageable debt levels
- You're currently working and can't attend full-time
- You need flexible scheduling to balance other commitments
- You live in an area without strong local programs
- You prefer self-directed learning and digital collaboration
- You want to minimize opportunity costs while earning your degree
- You already have strong quantitative skills and work experience
- You prefer hands-on learning through bootcamps and certifications
- You want to enter the field quickly without 2-year commitment
- You have financial constraints that make master's programs challenging
- You're exploring data science as a career transition
Return on Investment Analysis
Data science master's programs generally provide excellent return on investment, with graduates seeing significant salary increases that justify the educational investment within 3-5 years. However, ROI varies considerably based on program cost, career trajectory, and individual circumstances.
Public university programs offer the strongest ROI for most students. A typical graduate from UC Berkeley's MIDS program invests approximately $60,000 (including opportunity costs) but sees lifetime earnings increase by $800,000+ compared to bachelor's degree holders. Elite private programs command premium tuition but deliver exceptional outcomes for top performers, with some graduates earning $150,000+ in their first role.
Alternative Learning Paths
While master's degrees provide comprehensive education and credibility, alternative paths into data science continue to evolve. Data science bootcamps offer intensive 12-24 week programs focused on practical skills and job placement. These programs work well for career changers with strong quantitative backgrounds who want to transition quickly.
Self-directed learning through online courses, data analytics certifications, and practical projects can also lead to data science roles, especially for professionals with relevant work experience. However, master's degree holders typically have advantages in competitive job markets and earn higher starting salaries. Consider your background, career goals, and learning style when choosing between formal education and alternative paths.
Ranking Methodology and Data Sources
Our comprehensive ranking of 284 data science master's programs uses publicly available data from the Integrated Postsecondary Education Data System (IPEDS) 2023 and Bureau of Labor Statistics 2024 reports. We analyze program completion data using CIP code 30.7001 (Data Science/Data Analytics) and related interdisciplinary programs.
Ranking factors include career outcomes (35% weight) based on graduate employment rates and starting salary data, academic quality (30% weight) measuring faculty credentials and curriculum rigor, graduation rates (25% weight) from IPEDS completion statistics, and program value (10% weight) comparing tuition costs to career outcomes. All salary data is verified against BLS occupational employment statistics and institutional graduate outcome reports.
Frequently Asked Questions
Related Data Science Resources
Data Sources and References
U.S. Department of Education database providing comprehensive higher education statistics including enrollment, graduation rates, tuition, and program completion data.
Federal statistical data on employment and wage estimates for detailed occupations including data scientists (SOC 15-2051) and related technology roles.
Long-term employment projections showing expected job growth rates and annual job openings for data science and related occupations through 2032.
U.S. Department of Education database providing institution-level data on student outcomes, including graduation rates and post-graduation employment statistics.
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.