Search every machine learning degree program by what you actually want. All 185 accredited programs, ranked on real outcomes across bachelor's, master's, and online. $142,820 median salary with +35% projected job growth.
Accredited Programs185
Median Salary$142,820
Job Growth+35%
Annual Openings22,700+
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Key Takeaways
1.Hakia ranks the best machine learning degree programs in 2026, 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.
Yes, for the right candidates
Quick Answer: Is a Machine Learning Degree Worth It?
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 a methodology that considers graduation rates, program size, institutional reputation, and career outcomes. Rankings are updated annually using data from IPEDS and BLS.
Ranked #1 among artificial intelligence bachelor's programs by Hakia Score (95.4/100): 96% graduation rate, $128,105 median salary, $61,990 in-state tuition, 19 graduates a year. Federal data, IPEDS 2024 and BLS.
Ranked #2 among artificial intelligence bachelor's programs by Hakia Score (92.2/100): 94% graduation rate, $128,105 median salary, $64,596 in-state tuition, 45 graduates a year. Federal data, IPEDS 2024 and BLS.
Ranked #3 among artificial intelligence bachelor's programs by Hakia Score (87.8/100): 89% graduation rate, $128,105 median salary, $66,660 in-state tuition, 5 graduates a year. Federal data, IPEDS 2024 and BLS.
Ranked #4 among artificial intelligence bachelor's programs by Hakia Score (87.8/100): 83% graduation rate, $128,105 median salary, $9,718 in-state tuition, 1 graduates a year. Federal data, IPEDS 2024 and BLS.
Ranked #5 among artificial intelligence bachelor's programs by Hakia Score (82.5/100): 75% graduation rate, $128,105 median salary, $50,636 in-state tuition, 6 graduates a year. Federal data, IPEDS 2024 and BLS.
Ranked #6 among artificial intelligence bachelor's programs by Hakia Score (78.4/100): 80% graduation rate, $128,105 median salary, $10,622 in-state tuition, 2 graduates a year. Federal data, IPEDS 2024 and BLS.
Ranked #7 among artificial intelligence bachelor's programs by Hakia Score (72.6/100): 61% graduation rate, $128,105 median salary, $38,600 in-state tuition, 4 graduates a year. Federal data, IPEDS 2024 and BLS.
Ranked #8 among artificial intelligence bachelor's programs by Hakia Score (72/100): 74% graduation rate, $128,105 median salary, $51,444 in-state tuition, 1 graduates a year. Federal data, IPEDS 2024 and BLS.
Ranked #9 among artificial intelligence bachelor's programs by Hakia Score (70.9/100): 44% graduation rate, $128,105 median salary, $26,906 in-state tuition, 13 graduates a year. Federal data, IPEDS 2024 and BLS.
Ranked #10 among artificial intelligence bachelor's programs by Hakia Score (70.8/100): 71% graduation rate, $128,105 median salary, $25,620 in-state tuition, 1 graduates a year. Federal data, IPEDS 2024 and BLS.
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Program Strengths
71% graduation rate
$128,105 median salary
$25,620 in-state tuition
1 graduates annually
Best Machine Learning Programs - Top 10, Complete Program Data
#1. Massachusetts Institute of Technology — Bachelor's Artificial Intelligence
Hakia ranks Massachusetts Institute of Technology's bachelor's artificial intelligence program #1. Degree: Bachelor's. Delivery: on-campus. Location: Cambridge, MA | Type: Private nonprofit | Tuition: $61,990/year | Graduation Rate: 96% | Median Salary: $128,105 | Score: 95.4
#2. Carnegie Mellon University — Bachelor's Artificial Intelligence
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, 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.
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
🥇 #1
Massachusetts Institute of Technology
Bachelor's in Artificial IntelligenceOn-campus
Cambridge, MAPrivate nonprofit
$128,105 median salary · 96% grad rate · 19 grads/yr
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
🥇 #1
University of Pennsylvania
Master's in Artificial IntelligenceOn-campus
Philadelphia, PAPrivate nonprofit
$128,105 median salary · 97% grad rate · 87 grads/yr
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
🥇 #1
Carnegie Mellon University
Doctorate in Artificial IntelligenceFully online
Pittsburgh, PAPrivate nonprofit
$128,105 median salary · 94% grad rate · 35 grads/yr
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
🥇 #1
Wayne Community College
Associate's in Artificial IntelligenceOn-campus
Goldsboro, NCPublic
$128,105 median salary · 49% grad rate · 1 grads/yr
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.
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.
$95,000
Starting Salary
$142,820
Mid-Career
+35%
Job Growth
22,700
Annual Openings
Career Paths
Research Scientist
SOC 15-2041
+32%
Conduct advanced research in machine learning algorithms and AI applications in industry or academia.
Median Salary:$156,310
Computer Vision Engineer
SOC 15-1252
+28%
Specialize in algorithms that enable computers to interpret and process visual information.
Median Salary:$135,890
Machine Learning Curriculum Overview
ML programs 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
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 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.
Choose Machine Learning if.
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 advanced AI research and development
Choose Artificial Intelligence if.
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
Choose Data Science if.
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
Choose Computer Science if.
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
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
What can I do with a machine learning degree?
ML graduates work as AI/ML engineers, data scientists, research scientists, computer vision engineers, NLP specialists, robotics engineers, and AI product managers. Industries span tech companies, finance, healthcare, automotive, entertainment, and research institutions. See our AI/ML engineer salary guide for detailed career paths.
Do I need a PhD for machine learning careers?
No, most industry ML roles require master's degrees. PhDs are valuable for research scientist positions, leading R&D teams, or academic careers, but aren't necessary for most applied ML engineer or data scientist roles. Many successful ML professionals have master's degrees plus strong practical experience.
What programming languages should I learn for ML?
Python is the dominant language for machine learning, with libraries like TensorFlow, PyTorch, scikit-learn, and pandas. R is important for statistical analysis. SQL for database work. Some roles require C++ for performance optimization or Java for production systems. Start with Python and expand based on specialization.
How much math is required for machine learning?
Extensive math is essential: linear algebra (matrices, vectors, eigenvalues), multivariable calculus (gradients, optimization), probability theory, statistics (inference, hypothesis testing), and optimization theory. This is significantly more math-intensive than general software development or even most CS programs.
Can I get ML jobs without a machine learning degree?
It's possible but challenging. Many ML engineers have CS, mathematics, physics, or engineering degrees plus self-taught ML skills. However, formal ML education provides structured learning, research experience, and credibility that's valuable for competitive positions at top companies.
What's the difference between ML and AI degrees?
ML degrees focus specifically on algorithms that learn from data, neural networks, statistical learning, optimization. AI degrees are broader, covering robotics, computer vision, natural language processing, ethics, and cognitive science. ML is a subset of AI. Choose based on whether you want specialized depth or broader AI knowledge.
How long does a machine learning degree take?
Master's degrees take 1.5-2 years full-time. Professional master's programs for working students may take 2-3 years part-time. PhD programs take 4-6 years. Graduate certificates can be completed in 6-12 months. Duration depends on program structure and whether you're studying full-time or part-time.
What's the job market like for ML graduates?
Very strong. The BLS projects 35% growth through 2032 for AI/ML roles, among the fastest-growing careers. However, competition is intense for top positions, especially at major tech companies. Success requires strong technical skills, practical experience, and continuous learning as the field evolves rapidly. Entry-level positions often require 1-2 years of experience or exceptional academic projects.
Should I specialize in a specific area of ML?
After learning foundations, specialization can be valuable: computer vision, natural language processing, reinforcement learning, or domain applications (healthcare ML, financial ML, autonomous systems). Specialization often leads to higher compensation and more interesting work, but maintain breadth for career flexibility.
How important are internships for ML students?
Extremely important. ML is highly practical, and employers value hands-on experience. Internships at tech companies, research labs, or startups provide real-world project experience, industry connections, and often lead to full-time offers. Many programs require internships or significant project work for graduation.
How We Rank Machine Learning Degree Programs
Based on 742 programs from IPEDS 2024
We scored 18 machine learning programs on the Hakia Score, a 0 to 100 composite drawn from federal IPEDS 2024 and BLS figures, and Massachusetts Institute of Technology's Bachelor's in Artificial Intelligence sits at the top. 3 of them can be earned fully online.
Ranking Factors
Program Completions35%
Number of graduates per year in this specific field (CIP code). Larger programs indicate established departments with more resources, course offerings, and career services. Measured from IPEDS Completions data.
Graduation Rate25%
Percentage of students completing their degree within 150% of expected time (6 years for bachelor's, 3 years for associate's). Higher rates indicate better student support and program quality. Source: IPEDS Graduation Rates survey.
Selectivity20%
Admission rate (lower = more selective). More selective institutions have stronger academic environments and more competitive graduates. For open-admission institutions, we use graduation rates as a proxy for quality.
Career Outcomes20%
National salary data for machine learning graduates, factored into institutional scores based on job market strength.
Ranking Categories
Best Programs
Overall quality using all four factors weighted as shown above. Ideal for students seeking the strongest academic experience.
Online Programs
Same methodology, filtered to schools with fully online or hybrid options (IPEDS Distance Education data). Some schools may have lower graduation rates due to different student demographics.
Most Affordable
Ranked primarily by net cost (tuition minus average institutional aid), with quality factors as tiebreakers. Best for cost-conscious students.
Co-founder & Editor (B.S. Computer Science, Oregon State • B.A. Psychology, University of Washington)
Taylor combines technical expertise in computer science with a deep understanding of human behavior and learning. His dual background drives Hakia's mission: leveraging technology to build authoritative educational resources that help people make better decisions about their academic and career paths.
