- 1.Our top-ranked machine learning programs are University of Washington-Seattle Campus, Carnegie Mellon University, and University of Southern California—selected based on graduation rates, program size, and career outcomes.
- 2.Best value: University of Central Florida offers machine learning degrees at just $4,478/year with a 93% graduation rate.
- 3.91 accredited machine learning programs available nationwide, with options at every degree level from associate's to doctoral.
Source: BLS OEWS 2024, NSF 2024
Best Machine Learning Programs - Top 10
These are the best machine learning 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 Machine Learning Programs - Top 10
University of Washington-Seattle Campus
Doctoral: Very High Research (R1)
UW's engineering-focused AI/ML program is uniquely designed as a stackable degree system where working engineers can earn certificates that build toward a master's, with Boeing Company funding support and specializations spanning everything from robotics to materials science.
Program Overview
The University of Washington-Seattle Campus offers two distinct machine learning pathways: the Master of Science in Artificial Intelligence and Machine Learning for Engineering and the Master of Science in Data Science. The AI/ML for Engineering program is a flexible, stackable degree launching Fall 2026 that's specifically designed for working engineers who want to apply AI and ML to physical systems like manufacturing, robotics, and chemical processes. Built with Boeing Company funding support, this program can be completed fully online part-time or as a full-time student, combining foundational AI/ML skills with domain-specific training across multiple engineering disciplines. The complementary MSDS program has been operating since earlier and focuses on professional data science careers, meeting evenings on campus with an industry-relevant curriculum covering statistical modeling, data visualization, and software engineering. Both programs leverage UW's position as a top-10 global university with deep Seattle tech industry connections.
Degree Programs
Research Labs & Institutes
Real-time learning and control of complex dynamic systems
Data-driven discovery and control of dynamical systems
Data-intensive discovery across all fields using large, complex datasets
Scale-independent Multimodal Automated Real Time Systems
Location Advantages
- •Deep ties to Seattle tech industry
- •Four miles from downtown Seattle
- •Access to major employers like Amazon, Microsoft, Boeing
Industry Partners
Career Outcomes
JP Morgan Chase & Co., Parsons Corporation, IBM, Costco IT, Toyota
Admissions
Carnegie Mellon University
Doctoral: Very High Research (R1)
CMU houses the world's first academic machine learning department, founded in 2006, and has maintained the #1 ranking in artificial intelligence since 1997 according to U.S. News & World Report.
Program Overview
Carnegie Mellon's Master's in Machine Learning program emerges from the world's first academic machine learning department, founded in 2006. This intensive 16-month program can be completed in three semesters by motivated students, though many take four semesters to deepen their research experience or strengthen foundational skills. The curriculum demands six rigorous core courses spanning probabilistic graphical models to optimization theory, three specialized electives, and a full-time summer practicum that often leads to coveted industry positions. Students work alongside faculty who literally wrote the textbooks on machine learning, with access to cutting-edge research labs studying everything from deep reinforcement learning to AI ethics. The program welcomes students from diverse academic backgrounds - computer science majors study alongside physics PhDs and mathematics graduates - united by exceptional analytical skills and programming proficiency.
Degree Programs
Research Labs & Institutes
World's first academic ML department with research spanning theoretical foundations to real-world applications
Location Advantages
- •Pittsburgh's growing tech ecosystem
- •Proximity to major East Coast tech hubs
- •Strong connections to government research facilities
Industry Partners
Career Outcomes
Major technology companies, AI startups, Research institutions
Certifications & Designations
Admissions
University of Southern California
Doctoral: Very High Research (R1)
USC houses the MS in Computer Science - Artificial Intelligence, the first dedicated AI master's program in the United States, while its interdisciplinary approach uniquely combines machine learning with wireless communications, social impact applications, and entertainment industry connections in the heart of Los Angeles.
Program Overview
USC's Viterbi School of Engineering offers a comprehensive suite of machine learning and data science programs that bridge theoretical foundations with real-world applications. The flagship MS in Electrical and Computer Engineering - Machine Learning and Data Science provides focused, rigorous training in data science techniques, machine learning, and signal processing within the wireless communications domain. Complementing this is the MS in Computer Science - Artificial Intelligence, one of the nation's first dedicated AI master's programs, offering specialized tracks in deep learning, computer vision, natural language processing, and robotics. For students seeking broader data science foundations, the MS in Applied Data Science trains professionals from diverse backgrounds through hands-on experiences and a unique professional practicum, emphasizing practical skills in Python programming, database management, and big data infrastructure.
All programs require 32 units and can be completed in 1.5-2 years full-time. USC's machine learning ecosystem spans multiple research centers including the USC Center for Artificial Intelligence in Society, the Robotics and Autonomous Systems Center, and specialized labs like the Machine Learning and Data Mining Lab (Melady) and the Computational Social Science Laboratory. Students benefit from LA's tech corridor proximity and USC's extensive alumni network, with graduates placing at top-tier companies like Amazon, Google, Meta, and emerging AI startups.
Degree Programs
Research Labs & Institutes
AI applications for social good including combating human trafficking and wildlife conservation
Advanced machine learning algorithms and data mining techniques
Human-robot interaction, socially assistive robotics, and multi-robot systems
Data science applications in social sciences and network analysis
Machine learning applications in wireless communications
Location Advantages
- •Los Angeles tech ecosystem with proximity to major entertainment and aerospace industries
- •Strong connections to Silicon Beach startups and established tech companies
- •Year-round networking and internship opportunities in diverse industries
Industry Partners
Career Outcomes
Amazon, Google, Meta, Microsoft, Uber
Certifications & Designations
Admissions
Syracuse University
Doctoral: Very High Research (R1)
Syracuse University's iSchool has been pioneering information science education since 1928 and uniquely integrates human-centered design principles into AI education, ensuring graduates develop both cutting-edge technical skills and ethical frameworks for responsible AI deployment.
University of California-Irvine
Doctoral: Very High Research (R1)
Home to the world-famous UCI Machine Learning Repository with 688 datasets used by millions of researchers globally, plus the unique HPI Research Center partnership with Germany's leading tech institute launched in 2020.
Indiana University-Bloomington
Doctoral: Very High Research (R1)
IU's machine learning programs operate from the $35 million Luddy AI Center within the unique Mind, Brain, and Machine Quad, fostering unprecedented collaboration between AI researchers and cognitive scientists, psychologists, and neuroscientists.
University of Pennsylvania
Doctoral: Very High Research (R1)
Penn's MSE-AI is taught by some of the top AI researchers in the world and uniquely emphasizes ethical AI training alongside technical rigor, preparing graduates not just to build AI tools but to responsibly shape the future of this transformative technology.
University at Albany
Doctoral: Very High Research (R1)
UAlbany is one of the few universities to integrate topological data analysis as a core component of its data science curriculum, offering specialized training in this emerging field alongside traditional machine learning and statistics.
Massachusetts Institute of Technology
Doctoral: Very High Research (R1)
MIT pioneered many foundational concepts in artificial intelligence and machine learning, housing CSAIL - one of the world's largest and most influential AI research laboratories - where faculty and students work alongside the creators of fundamental algorithms that power modern ML systems.
New York University
Doctoral: Very High Research (R1)
NYU houses Yann LeCun's legendary CILVR lab and created the world's first 'AI degree' through its MS in Emerging Technologies program, where every student must demonstrate AI fluency regardless of their chosen specialization.
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 →
Who Should Study Machine Learning?
Machine learning is ideal for students with strong mathematical backgrounds who enjoy working with data, algorithms, and statistical analysis. Success requires comfort with linear algebra, calculus, statistics, and programming—typically requiring prior computer science or data science coursework.
- Strong mathematical foundation in linear algebra, calculus, probability, and statistics
- Programming experience in Python, R, or similar languages used in data science
- Analytical mindset with interest in pattern recognition and data-driven insights
- Research orientation—many ML roles involve experimental work and hypothesis testing
- Persistence and curiosity—ML involves extensive experimentation and iterative improvement
Most successful ML students have undergraduate degrees in computer science, mathematics, physics, engineering, or related quantitative fields. Career changers should consider building foundations through AI/ML bootcamps or data science programs first.
Machine Learning Programs by Degree Level
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
Machine Learning Programs by Degree Level
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 Machine Learning Programs - Bachelor's
A bachelor's degree in machine learning is the standard credential for entry-level positions. These 4-year programs provide comprehensive training and hands-on experience.
Best Machine Learning Programs - Top 3 Bachelor's
University of Washington-Seattle Campus
303 graduates, 97% grad rate, Score: 97.5
Carnegie Mellon University
33 graduates, 98% grad rate, Score: 85.0
University of California-Irvine
90 graduates, 96% grad rate, Score: 75.3
4. University of Southern California (Los Angeles, CA) - Score: 75.1, Tuition: $66,640
5. Indiana University-Bloomington (Bloomington, IN) - Score: 74.0, Tuition: $10,312
6. University at Albany (Albany, NY) - Score: 72.8, Tuition: $7,070
7. Massachusetts Institute of Technology (Cambridge, MA) - Score: 70.6, Tuition: $59,750
8. University of Michigan-Ann Arbor (Ann Arbor, MI) - Score: 68.6, Tuition: $17,977
9. University of Massachusetts-Amherst (Amherst, MA) - Score: 64.1, Tuition: $16,591
10. Rochester Institute of Technology (Rochester, NY) - Score: 62.7, Tuition: $55,784
Best Machine Learning Programs - Master's
A master's degree in machine learning prepares students for senior and specialized roles. These 1-2 year programs offer advanced expertise and leadership training.
Best Machine Learning Programs - Top 3 Master's
Carnegie Mellon University
178 graduates, 98% grad rate, Score: 94.4
University of Southern California
357 graduates, 92% grad rate, Score: 92.5
Syracuse University
233 graduates, 99% grad rate, Score: 84.3
4. University of Washington-Seattle Campus (Seattle, WA) - Score: 81.7, Tuition: $11,524
5. University of Pennsylvania (Philadelphia, PA) - Score: 73.7, Tuition: $58,620
6. New York University (New York, NY) - Score: 70.5, Tuition: $60,438
7. Northwestern University (Evanston, IL) - Score: 67.5, Tuition: $64,887
8. Clark University (Worcester, MA) - Score: 66.2, Tuition: $54,760
9. University of California-Irvine (Irvine, CA) - Score: 65.7, Tuition: $11,834
10. Northeastern University (Boston, MA) - Score: 65.4, Tuition: $62,000
Best Machine Learning Programs - Online
Online machine learning programs offer flexibility for working professionals. Top accredited programs provide the same curriculum quality as on-campus alternatives.
Best Machine Learning Programs - Top 3 Online
University of Washington-Seattle Campus
303 graduates, 97% grad rate, Score: 97.5
Carnegie Mellon University
33 graduates, 98% grad rate, Score: 85.0
Syracuse University
233 graduates, 99% grad rate, Score: 84.3
4. University of California-Irvine (Irvine, CA) - Score: 75.3, Tuition: $11,834
5. University of Southern California (Los Angeles, CA) - Score: 75.1, Tuition: $66,640
6. Indiana University-Bloomington (Bloomington, IN) - Score: 74.0, Tuition: $10,312
7. University of Pennsylvania (Philadelphia, PA) - Score: 73.7, Tuition: $58,620
8. University at Albany (Albany, NY) - Score: 72.8, Tuition: $7,070
9. Massachusetts Institute of Technology (Cambridge, MA) - Score: 70.6, Tuition: $59,750
10. New York University (New York, NY) - Score: 70.5, Tuition: $60,438
Best Machine Learning Programs - Associate's
An associate's degree in machine learning 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 Machine Learning Programs - Top 3 Associate's
Weber State University
139 graduates, 92% grad rate, Score: 64.5
Rochester Institute of Technology
3 graduates, 90% grad rate, Score: 59.4
Santa Monica College
46 graduates, 95% grad rate, Score: 55.7
4. Southern New Hampshire University (Manchester, NH) - Score: 54.4, Tuition: $15,450
5. Green River College (Auburn, WA) - Score: 53.5, Tuition: $4,074
6. Utah Valley University (Orem, UT) - Score: 53.0, Tuition: $5,614
7. CUNY New York City College of Technology (Brooklyn, NY) - Score: 52.5, Tuition: $6,930
8. MiraCosta College (Oceanside, CA) - Score: 52.4, Tuition: $1,104
9. Columbia Basin College (Pasco, WA) - Score: 51.3, Tuition: $5,514
10. De Anza College (Cupertino, CA) - Score: 51.0, Tuition: $1,395
Best Machine Learning Programs - Graduate
Graduate programs in machine learning (PhD and doctoral degrees) prepare students for research, academic, and senior leadership positions.
Best Machine Learning Programs - Top 3 Graduate
Carnegie Mellon University
28 graduates, 98% grad rate, Score: 90.0
University of California-Irvine
3 graduates, 96% grad rate, Score: 66.0
Indiana University-Bloomington
19 graduates, 84% grad rate, Score: 60.3
4. University of Florida (Gainesville, FL) - Score: 60.2, Tuition: $4,477
5. Clemson University (Clemson, SC) - Score: 60.0, Tuition: $14,038
6. Pennsylvania State University-Main Campus (University Park, PA) - Score: 58.8, Tuition: $19,672
7. Northern Arizona University (Flagstaff, AZ) - Score: 57.7, Tuition: $11,015
8. University of Pittsburgh-Pittsburgh Campus (Pittsburgh, PA) - Score: 56.3, Tuition: $20,154
9. Capitol Technology University (Laurel, MD) - Score: 55.8, Tuition: $26,088
10. University of Iowa (Iowa City, IA) - Score: 53.8, Tuition: $9,016
Most Affordable Machine Learning Programs
Looking for quality machine learning 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 Machine Learning Programs
| Rank | Institution | Location | Tuition | Value Score | Grad Rate |
|---|---|---|---|---|---|
| 1 | University of Central Florida | Orlando, FL | $4,478 | 122.8 | 93% |
| 2 | University of Louisiana at Lafayette | Lafayette, LA | $5,407 | 111.3 | 98% |
| 3 | San Jose State University | San Jose, CA | $5,742 | 109.9 | 100% |
| 4 | University of North Florida | Jacksonville, FL | $3,996 | 107.2 | 82% |
| 5 | Florida Atlantic University | Boca Raton, FL | $2,522 | 106.2 | 77% |
Machine Learning Career Outcomes
Machine learning offers some of the highest-paying and fastest-growing careers in technology. The BLS projects 35% job growth for data scientists and AI/ML roles through 2032—much faster than average. For detailed compensation analysis, see our AI/ML engineer salary guide.
Career Paths
AI/ML Engineer
SOC 15-2051Design and implement machine learning models and AI systems for production applications.
Data Scientist
SOC 15-2051Apply statistical analysis and machine learning to extract insights from complex datasets.
Research Scientist
SOC 15-2041Conduct advanced research in machine learning algorithms and AI applications in industry or academia.
Software Engineer (AI/ML)
SOC 15-1252Develop software applications that incorporate machine learning capabilities and AI features.
Computer Vision Engineer
SOC 15-1252Specialize in algorithms that enable computers to interpret and process visual information.
Machine Learning Curriculum Overview
ML programs typically combine computer science theory, advanced mathematics, and practical implementation. Core areas include statistical learning theory, optimization, algorithms, and hands-on experience with real-world datasets.
- Mathematical Foundations: Linear algebra, multivariate calculus, probability theory, statistics
- Core ML: Supervised learning, unsupervised learning, reinforcement learning, neural networks
- Programming: Python/R programming, TensorFlow/PyTorch, scikit-learn, data manipulation
- Theory: Statistical learning theory, optimization methods, computational complexity
- Applications: Computer vision, natural language processing, robotics, recommender systems
- Research Methods: Experimental design, model evaluation, research methodology, thesis/capstone
Most programs require significant project work, often culminating in a thesis or capstone project involving original research or industry collaboration. Internships at tech companies or research labs are highly encouraged.
Machine Learning Programs by State
Arizona
California
Colorado
Florida
Georgia
Illinois
Massachusetts
Michigan
New York
North Carolina
Ohio
Pennsylvania
Texas
Virginia
Washington
Connecticut
Indiana
Maryland
Minnesota
Missouri
New Jersey
Oregon
Tennessee
Utah
Wisconsin
Machine Learning vs Related Fields
Machine learning is the most mathematically intensive computing field. Success requires genuine comfort with linear algebra, calculus, probability theory, and optimization—not just using libraries, but understanding why algorithms work and when they'll fail.
ML distinguishes itself from traditional programming through its empirical nature. Rather than writing explicit rules, you design experiments, tune hyperparameters, analyze results, and iterate. This scientific approach requires patience with ambiguity and comfort with experimentation.
The field is highly competitive, with top positions requiring exceptional mathematical ability and research experience. However, many valuable ML roles exist that don't require PhD-level expertise—applied ML engineers who deploy and maintain models, ML ops specialists, and domain experts who apply ML to specific industries.
Which Should You Choose?
- You want to specialize specifically in ML algorithms and applications
- You have strong math/stats background and enjoy theoretical work
- Your goal is ML engineer, research scientist, or data scientist roles
- You're interested in cutting-edge AI research and development
- You want broader AI knowledge including robotics, NLP, computer vision
- You're interested in AI ethics, policy, and societal implications
- You prefer interdisciplinary approach over pure technical focus
- You want flexibility across various AI application areas
- You want to focus on business insights and analytics over algorithms
- You prefer working with business stakeholders and domain experts
- You're more interested in descriptive/predictive analytics than AI
- You want roles in traditional industries undergoing digital transformation
- You want maximum career flexibility across all tech roles
- You're unsure about specializing in AI/ML specifically
- You want strong software engineering foundations
- You prefer broader computer science theory and applications
Is a Machine Learning Degree Worth It?
For students with appropriate backgrounds and career goals, yes. The combination of high salaries ($95,000+ starting, $142,820+ mid-career), exceptional job growth (35%), and expanding applications across industries makes ML degrees highly valuable for the right candidates.
When it's worth it: You have strong mathematical foundations, programming experience, genuine interest in AI/ML research or applications, and career goals aligned with ML engineering, data science, or research roles.
When to consider alternatives: You lack mathematical prerequisites (consider CS first), want general software development careers (CS may be better), have budget constraints (bootcamps or online courses), or prefer applied work over research-oriented roles.
The field is highly competitive and requires continuous learning as technologies evolve rapidly. Success depends on strong technical foundations, practical experience, and staying current with research developments.
Alternative Paths to Machine Learning Careers
While ML degrees provide comprehensive education, alternatives exist for different goals and timelines
- AI & Machine Learning Bootcamps — Intensive programs for career switchers with technical backgrounds
- AI/ML Certifications — Professional credentials for specific skills and technologies
- Computer Science Master's with AI track — Broader CS foundation plus ML specialization
- Data Science Degrees — Focus on analytics with some ML components
- Self-study through online courses, books, and projects — Requires strong self-direction
Many professionals combine approaches—starting with online courses or bootcamps, then pursuing formal education for advancement. For detailed guidance, see How to Become an AI Engineer.
Machine Learning Degree FAQ
Based on 485 programs from IPEDS 2023, BLS OES 2024, NSA CAE Database
Number of machine learning 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
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