Computer science is the defining discipline of the 21st-century economy. The systematic study of computation, meaning algorithms, data structures, operating systems, programming languages, artificial intelligence, machine learning, networks, and the theoretical foundations of information processing, underlies nearly every sector of the modern economy and has produced more wealth, more disruption, and more demand for skilled graduates than any other academic field of the past four decades. A CS degree today is at once the most employable technical credential in higher education, a gateway to doctoral research at the frontier of artificial intelligence and systems, and an intellectual discipline with real depth in discrete mathematics, logic, and the theory of computation.
Approximately 41,900 computer science bachelor’s degrees are awarded annually under CIP 11.07, across 360 programs that meet the inclusion threshold of 30 degrees over three years. This makes CS the largest technical field in the College Transitions ranking series by a wide margin. It is also the highest-earning. CS graduates post median field-of-study earnings, measured four years after graduation in the College Scorecard, that run more than double those of most other disciplines in this series, from roughly $71,000 at the low end of ranked programs to $256,539 at Harvard. Those earnings create a distinctive Earnings & ROI (C4) dynamic: the spread between programs is wider than in any other field, and the programs that lead on earnings are largely the same ones that lead on academic quality and PhD production.
College Transitions has developed a data-driven ranking of the top 100 undergraduate computer science programs, applying the same five-component methodology used across this ranking series with a program-level two-tier Earnings & ROI component.
How We Built the Ranking
The approach evaluates all 360 scoreable institutions across five components.
| Component | Weight | Data Source / Notes |
| Major Emphasis | 12% | IPEDS Degree Completions (CIP 11.07) |
| Program Scale | 13% | IPEDS Degree Completions (log) |
| Academic Rating | 30% | IPEDS / Common Data Set |
| Earnings & ROI (Tier 1) | 25% | CS field earnings 55% + inst. 15% + ROI 20yr 15% + ROI 40yr 15% (61.9% coverage) |
| Earnings & ROI (Tier 2†) | 25% | Inst. earnings 55% + ROI 20yr 22.5% + ROI 40yr 22.5% (116 programs) |
| PhD Productivity | 20% | NSF Survey of Earned Doctorates: “Computer science” field |
Two-tier note: Tier 1 uses CS-specific field earnings where Scorecard coverage exists; Tier 2 (†) uses institution-level earnings and ROI for the 116 programs where CS-specific field earnings fall below Scorecard disclosure thresholds.
CS field earnings are the widest-ranging in this ranking series. The range of CS-specific Scorecard earnings across programs, from roughly $71,000 to $256,539 measured four years after graduation, is far wider than in any other field we have ranked. Harvard’s $256,539 median reflects CS graduates entering quantitative finance, software engineering at major technology companies, and consulting at rates that drive exceptional early-career earnings. The top eight CS earnings programs, Harvard ($256,539), CMU ($247,552), Brown ($218,525), Stanford ($200,950), MIT ($199,774), Cornell ($185,679), Harvey Mudd ($183,524), and UC Berkeley ($178,867), form a tier where graduates’ direct-employment earnings four years out already exceed the long-horizon ROI figures of graduates from most other academic fields. This concentration reflects the technology industry’s recruitment of graduates from a small number of programs, a measurable quality differential the Earnings & ROI component captures.
Princeton (#2) and Caltech (#10) are Tier 2 on C4 despite being among the most selective and research-productive CS programs in the country. This mirrors the pattern seen in astronomy, physics, and other research-intensive fields at elite institutions: when a large enough fraction of graduates proceed to doctoral programs or directly to high-compensation industry roles, the remaining direct-employment cohort falls below Scorecard disclosure thresholds. Their Tier 2 status should be read as a quality signal, not a deficiency.
The Top 25
The top 25 programs are shown below. The CS ranking is the most heavily concentrated at the elite tier of any field in this series. The gap between #1 MIT (95.5) and #25 Maryland (84.5) is only 11 composite points, a sign that the most selective programs in the country all have exceptional CS programs with outstanding earnings, PhD pipelines, and academic environments. Below #25, the scores spread out.
| Rank | Institution | State | Type | C4 | Score |
| 1 | Massachusetts Institute of Technology | MA | Tech | T1 | 95.5 |
| 2 | Princeton University | NJ | Private | T2† | 95.3 |
| 3 | Duke University | NC | Private | T1 | 94.3 |
| 4 | Stanford University | CA | Private | T1 | 93.8 |
| 5 | Carnegie Mellon University | PA | Tech | T1 | 93.7 |
| 6 | Harvard University | MA | Private | T1 | 93.5 |
| 7 | Cornell University | NY | Private | T1 | 93.3 |
| 8 | Brown University | RI | Private | T1 | 93.0 |
| 9 | Columbia University | NY | Private | T1 | 92.2 |
| 10 | California Institute of Technology | CA | Tech | T2† | 91.4 |
| 11 | University of Chicago | IL | Private | T1 | 90.9 |
| 12 | Dartmouth College | NH | LAC | T1 | 88.7 |
| 13 | Harvey Mudd College | CA | LAC | T1 | 88.5 |
| 14 | Vanderbilt University | TN | Private | T1 | 87.9 |
| 15 | Northwestern University | IL | Private | T1 | 87.5 |
| 16 | Rensselaer Polytechnic Institute | NY | Tech | T1 | 87.4 |
| 17 | University of California-Berkeley | CA | Public | T1 | 87.4 |
| 18 | Tufts University | MA | Private | T1 | 87.1 |
| 19 | Worcester Polytechnic Institute | MA | Tech | T1 | 87.0 |
| 20 | University of Southern California | CA | Private | T1 | 85.8 |
| 21 | Williams College | MA | LAC | T1 | 85.7 |
| 22 | University of Pennsylvania | PA | Private | T1 | 85.2 |
| 23 | Pomona College | CA | LAC | T1 | 85.0 |
| 24 | University of Rochester | NY | Private | T1 | 84.6 |
| 25 | University of Maryland-College Park | MD | Public | T2† | 84.5 |
Table 1. Top 25 Undergraduate Computer Science Programs, 2026 College Transitions Ranking. † = Tier 2 C4 (Earnings & ROI). LAC = Liberal Arts College.
MIT (#1, 95.5) leads the ranking with strong scores across all five components: 99.7 on Major Emphasis (CS accounts for more of MIT’s total degrees than at virtually any comparable research university), 94.4 on Program Scale (485 CS degrees over three years), 88.3 on Academic Rating, 99.3 on Earnings & ROI (CS field earnings of $199,774), and a near-perfect 99.6 on PhD Productivity (158 CS doctoral recipients at 34.5 per 1,000, among the highest per-capita rates of any major research university). MIT’s EECS (Electrical Engineering and Computer Science) department, which houses the CS undergraduate program, is one of the most research-intensive CS environments in the world by many measures, including faculty ACM Turing Award count, NSF grant volume, and placement at leading technology companies.
Princeton (#2, 95.3)† posts the highest Academic Rating in the full 360-program dataset (94.0), 99.7 on Earnings & ROI (reflecting its high institutional earnings and ROI), and 98.3 on PhD Productivity (69 doctoral recipients at 12.2 per 1,000). Princeton’s Department of Computer Science has particular strengths in algorithms and complexity theory, programming languages, security, and AI/ML, with a research culture that emphasizes theoretical depth alongside practical application. Its Tier 2 C4 status reflects that Princeton CS graduates disproportionately proceed to elite doctoral programs or high-compensation industry roles that collectively suppress the Scorecard field-earnings disclosure.
Duke (#3, 94.3) is the ranking’s most analytically notable result. Duke scores 93.6 on Major Emphasis, 89.2 on Program Scale, 93.4 on Academic Rating (second-highest in the dataset), 96.4 on Earnings & ROI (CS field earnings of $159,845), and 96.5 on PhD Productivity (56 CS doctoral recipients). Duke’s Department of Computer Science has grown substantially in faculty depth and student demand over the past decade, building particular strengths in AI, machine learning, systems, and human-computer interaction. For students who prioritize an elite academic environment, Duke’s combination of CS depth and overall institutional quality is an exceptional option.
Carnegie Mellon (#5, 93.7) is the program most often cited as the top CS school in the country by other rankings, and the data backs its prominence. CMU scores 99.2 on Earnings & ROI (CS field earnings of $247,552, second-highest in the dataset), 99.3 on PhD Productivity (110 doctoral recipients at 14.3 per 1,000, a high per-capita rate for a program of its scale), and strong marks on Major Emphasis (95.8) and Program Scale (86.7). CMU’s School of Computer Science, which houses multiple departments including one of the premier machine learning departments in the world, gives undergraduates accessible research engagement at the frontier of the field. Its #5 position rather than #1 reflects that MIT, Princeton, Duke, and Stanford score higher on Academic Rating or on the combination of earnings and PhD pipeline, not any deficiency in CMU’s program.
Harvey Mudd College (#13, 88.5) posts the highest per-capita PhD rate among all programs producing 30 or more CS doctoral recipients (47.8 per 1,000 undergraduates), a 99.4 Major Emphasis score (CS is central to Harvey Mudd’s identity), and 99.0 on Earnings & ROI (CS field earnings of $183,524). Harvey Mudd’s CS program is exceptional for its size: every student works closely with faculty, the curriculum is among the most rigorous for undergraduates in the country, and its per-capita placement at top graduate programs and technology companies rivals MIT and CMU. For a student who wants a small, intensely academic setting for CS rather than a large research university, Harvey Mudd is the strongest option in the country.
RPI (#16, 87.4) and WPI (#19, 87.0) are the two highest-ranking technical institutes outside the top-tier private and Ivy-adjacent group. RPI scores 98.9 on Major Emphasis and 96.7 on PhD Productivity (44 CS doctoral recipients); WPI scores 98.3 on Major Emphasis and 85.8 on Program Scale. Both reflect the distinctive CS culture of technical institutes: students are surrounded by STEM peers, CS is a first-class institutional priority, and the curriculum is oriented toward both research preparation and industry employment.
What Separates the Best Programs?
The Liberal Arts College Tier: Dartmouth, Harvey Mudd, Williams, Pomona, Carleton
Five liberal arts colleges rank in the top 35: Dartmouth (#12), Harvey Mudd (#13), Williams (#21), Pomona (#23), and Carleton (#32). This is the first ranking in this series where two LACs (Dartmouth and Harvey Mudd) rank in the top 15 of a STEM field, a sign of the unusually strong alignment between CS and the liberal arts college research-mentorship model.
Dartmouth (#12, 88.7) scores 91.1 on Major Emphasis and 96.0 on Earnings & ROI (CS field earnings of $157,053, reflecting the Wall Street and technology premium for Dartmouth graduates). Its 90.1 PhD Productivity score rests on 29 CS doctoral recipients at a strong per-capita rate. Dartmouth’s CS department has particular strengths in human-computer interaction, privacy and security, and the intersection of CS and social science, consistent with its liberal arts identity inside a research university.
UC Berkeley and the Large Public University Tier
UC Berkeley (#17, 87.4) scores 99.4 on Program Scale (2,380 CS degrees over three years, the largest program by degree count in the dataset) and 97.6 on PhD Productivity (178 CS doctoral recipients, the highest raw count in the dataset). Berkeley’s EECS program is the strongest public-university CS environment in the country by most measures, including NSF grant volume, ACM award count, and industry placement. Its composite rank of #17 reflects that its Academic Rating (67.5, a function of its large and somewhat less selective overall admissions profile) and field earnings ($178,867, strong but below the elite private programs) limit its composite relative to the top 10.
UIUC (#34), University of Washington (#36), and University of Maryland (#25) complete the tier of major public research universities with nationally recognized CS programs. UIUC posts 101 CS doctoral recipients (the fourth-highest raw count) and has particular strength in programming languages, systems, and databases, three areas of high industry demand. Washington’s Paul G. Allen School of Computer Science & Engineering has particular strength in AI/ML and systems, aided by its proximity to the Microsoft and Amazon headquarters. Maryland’s Department of Computer Science benefits from its proximity to NSA, NIST, and the broader federal technology community in the D.C. metro area.
What $200K+ CS Earnings Mean
The CS earnings data in this ranking are categorically different from any other field. Harvard’s $256,539 median, measured four years after graduation, is the highest field-of-study earnings figure in the entire College Scorecard, above the early-career median for graduates of essentially any other undergraduate program in any field. CMU’s $247,552 reflects that the major technology companies (Google, Meta, Apple, Microsoft, Amazon) and the quantitative hedge funds that recruit engineers compete for CMU CS graduates with packages of base salary, stock, and bonus that can total $200,000 to $400,000 for new graduates. The spread between the top programs ($256,539 at Harvard) and the typical program (near $90,000 four years out) is not explained by skill differences alone. It reflects the network effects of elite-program placement at the highest-compensation employers, which have historically concentrated at a small number of institutions.
Patterns, Themes, and What They Mean for Your Students
Computer science is at once the highest-earning and one of the most intellectually rigorous undergraduate majors. Counselors should resist the framing of CS as a purely vocational choice. The discipline’s theoretical foundations, computability theory, complexity theory, algorithm design, formal verification, and the mathematics of information, are demanding and require the same capacity for abstract reasoning as mathematics or physics. Students drawn to CS mainly by earnings expectations but who lack real mathematical ability or curiosity about computation will struggle at selective programs. The students who thrive, and who ultimately earn the salaries the top programs’ earnings data reflects, are those who find the intellectual problems of computation compelling in their own right.
The CS job market rewards selectivity of training institution more than almost any other field. In most professional fields, the marginal value of attending a top-20 rather than a top-100 program is real but modest. In CS, the concentration of elite employer recruiting at a small number of programs creates a much larger differential. Google, Meta, Apple, and the major quantitative hedge funds (Two Sigma, Renaissance Technologies, Citadel) conduct on-campus recruiting primarily at MIT, CMU, Stanford, Berkeley, Cornell, and a small number of other programs. That produces a premium for graduates of these programs that is visible in the earnings data and that counselors should be candid with students about when discussing CS program choice.
The artificial intelligence boom is the most significant factor reshaping the CS program landscape. The surge in industry demand for machine learning engineers, AI researchers, and data scientists since the mid-2010s has reshaped CS hiring, curriculum, and faculty composition at every ranked program. Programs with the deepest AI/ML research faculty, MIT (CSAIL), CMU (Machine Learning Department), Stanford (HAI), Berkeley (BAIR), Cornell Tech, and Princeton, have the strongest positioning for the career paths driving the field’s earnings premium. Students should specifically ask about AI/ML research opportunities and faculty depth when evaluating programs.
Co-op and industry experience matter more in CS than in most other technical fields. The gap between academic CS training and industry CS practice is wider than in most disciplines. A student who has completed two or three meaningful software engineering internships at real companies arrives at graduation with industry credibility that pure academic performance cannot replicate. Programs at Northeastern (co-op), WPI (project-based learning), and Drexel (co-op) explicitly integrate professional experience into the degree. Even at programs without formal co-op requirements, students should pursue summer internships aggressively beginning in their first or second year.
Computer science is the discipline reshaping every other discipline. Biology, medicine, physics, economics, the humanities, and the social sciences are all being transformed by the computational tools that CS produces. The programs that lead this ranking have built the faculty, research infrastructure, and industry relationships that give undergraduates access to that transformation at the level it demands. Students who choose their CS program carefully, attending to research culture, AI/ML depth, industry placement data, and doctoral-pipeline strength alongside institutional prestige, will find a field with unmatched career prospects and intellectual rewards at the highest level.
