12 Top Machine Learning Masters Programs for 2026 (Expert Rankings)
The right machine learning masters programs can transform your career trajectory, especially when you have some options that cost under $9,000 for the entire degree. The just need for specialized ML expertise has sparked a surge in quality graduate programs across the country.
Masters programs in machine learning now cater to working professionals who want to apply their programming skills to advanced ML applications. Whether you’re learning about campus-based or machine learning masters degree online formats, this piece ranks 12 top programs based on curriculum strength, faculty expertise, tuition value, and career outcomes to help you make an informed decision.
Georgia Institute of Technology – Online Master of Science in Computer Science (Machine Learning Specialization)
Program Overview and Format
Georgia Tech’s OMSCS represents one of the most available machine learning masters programs you can find. The program delivers all coursework asynchronously and allows you to view lectures and complete assignments on your schedule. You can enroll in one course per semester. The degree can take up to six years to finish. Working professionals who just need to balance education with machine learning career find this flexibility suitable.
Key Features and Curriculum
The program requires 30 total credit hours (10 courses) to graduate. You must complete one specialization requiring 15 to 18 credit hours within this structure. The Machine Learning specialization requires 15 hours split between core requirements and electives.
Core courses have two mandatory components: one algorithms course (CS 6515 Introduction to Graduate Algorithms being the online option) and one ML foundation course (CS 7641 Machine Learning or CSE 6740 Computational Data Analysis). You’ll then select three electives from options like Computer Vision, Deep Learning, Reinforcement Learning, and Natural Language Processing. The remaining 15 hours consist of free electives from any OMSCS offerings.
All courses counting toward your specialization require grades of B or higher. A minimum grade of C applies to other coursework. You must maintain a cumulative GPA of 3.0 to graduate.
Admission Requirements
The program prefers applicants with undergraduate degrees in computer science or related fields (mathematics, computer engineering, electrical engineering) with a cumulative GPA of 3.0 or higher. Applicants not meeting these criteria receive case-by-case evaluation.
You must hold a bachelor’s degree from a regionally accredited institution before matriculation. International applicants need satisfactory TOEFL or IELTS-Academic scores. After enrolling, you face a foundational coursework requirement: complete 2 designated foundational courses with grades of B or better within your first 12 months.
Tuition and Cost
The program costs $301 per credit hour, which has a $180 tuition fee, $107 technology fee, and (as of 2022) no special institutional fee. Total tuition amounts to $9,030 for the complete 30-credit degree. Most students take 5-7 semesters to graduate. Actual costs range from $5,935 to $6,149.
What Makes This Program Stand Out
This program delivers the same curriculum and rigor as Georgia Tech’s on-campus degree while maintaining exceptional affordability. The university graduated 10,000 alumni in the program’s first 10 years. The asynchronous structure means you’re never locked into specific class times, unlike traditional formats. This accommodates various time zones and work schedules.
Carnegie Mellon University – Master of Science in Machine Learning
Program Overview and Format
Carnegie Mellon’s Machine Learning Department has spent over 25 years defining the field of machine learning and artificial intelligence. The MS in Machine Learning runs as an intensive on-campus program that requires physical presence in Pittsburgh. You can complete the degree in 16 months over three semesters, though some students extend to four semesters to pursue research or strengthen foundational skills.
Domestic students can study part-time while attending classes. International students on student visas must finish within three semesters by December. The program accepts applications only in December to start in August.
Key Features and Curriculum
The program requires 111 total units: six core courses, three electives and a practicum. You’ll take all six cores from separate course lines. These have one introductory machine learning course (10-701 or 10-715), one deep learning option (10-617 Intermediate Deep Learning, 10-703 Deep Reinforcement Learning, or 10-707 Advanced Deep Learning), 10-708 Probabilistic Graphical Models, 10-718 Machine Learning in Practice, 10-725 Optimization for Machine Learning and one probability/statistics course (36-700 or 36-705).
The three electives draw from options like Machine Learning with Large Datasets, Machine Learning Ethics and Society, Generative AI, Advanced Machine Learning Theory and specialized topics in healthcare, neuroscience and natural language processing. You’ll complete a one-semester full-time practicum during summer, with either an internship or research related to machine learning.
Admission Requirements
You need a strong background in computer science, specifically solid understanding of complexity theory and good programming skills. The mathematics requirement has at least one year of college-level probability and statistics, plus matrix algebra and multivariate calculus. Programming experience in Matlab, R, scipy-numpy, Java or Python proves helpful.
GRE scores are optional to apply in Fall 2025 and start in August 2026. The program welcomes applicants from varied backgrounds and does not require a computer science undergraduate degree.
Tuition and Cost
The first-year tuition costs $54,420. The program provides no financial support. You must cover tuition, student fees and living expenses on your own.
What Makes This Program Stand Out
The department’s defining characteristic centers on the rapid transition from theory to practice. Research spans domains that have AI intersections with biology, health and education, united by ground effect. Students work with accomplished peers in a research-oriented environment where professors cooperate with master’s students.
University of Washington – Online MS in AI and Machine Learning for Engineering
Program Overview and Format
The University of Washington structures this degree around a stacked credential model where you begin with graduate certificates and progress toward a full master’s degree. You can complete the entire program online on a part-time basis, though full-time enrollment remains available. This design targets working engineers who need to apply AI and ML methods to applications with physical constraints like manufacturing, chemical processes and robotics.
The stacked format means you first enroll in a stackable graduate certificate, then add certificates before completing a two-quarter capstone sequence to earn your master’s degree. This structure provides flexibility to stop after earning certificates or continue building toward the full degree.
Key Features and Curriculum
You’ll complete domain-specific training tailored to your particular field beyond foundational AI and ML skills applicable in engineering disciplines. The program emphasizes implementing appropriate AI and ML methods for specific engineering applications while learning to review results responsibly. You’ll strengthen mathematics and coding skills to create a foundation for adapting to evolving AI tools throughout your career.
The capstone sequence spans two quarters and requires you to apply techniques learned to complex or novel use cases while advancing project management capabilities. Each stackable certificate contains 16 credits and takes approximately nine months to complete part-time.
Admission Requirements
You need a 3.0 cumulative GPA on a 4.0 scale from an accredited institution. Specific coursework requirements include calculus, differential equations, linear algebra and physics at the undergraduate level, plus either coursework or work experience writing computer code in any language. The program recommends an undergraduate major in engineering, physics, chemistry or related disciplines, though other majors receive consideration if prerequisite coursework is complete.
Your application requires a resume, statement of purpose, one letter of recommendation and unofficial transcripts. The application deadline falls on June 1st. The program cannot accept F1/J1 international students requiring an I-20/DS-2019 to enroll, though students completing the degree online while outside the United States are eligible.
Tuition and Cost
Total program costs range between $40,375 and $43,088 for the 2025-26 academic year. The final cost depends on which domain-specific certificate you select for your second certificate requirement.
What Makes This Program Stand Out
The mostly asynchronous format allows you to learn when it fits your schedule. Faculty expertise spans machine learning combined with traditional engineering disciplines including robotics, materials, dynamics and control, and industrial design.
Columbia University – Online Master of Science in Computer Science (Machine Learning Track)
Program Overview and Format
Columbia Engineering delivers its machine learning master’s degree online through CVN (Columbia Video Network). You can pursue a fully accredited degree without campus residency. The program requires 30 points of coursework at the 4000 level or above while you maintain a 2.7 overall GPA. All requirements must be completed within five years from your first course. The format allows you to view lectures anytime and anywhere. Professionals in different time zones can participate.
Key Features and Curriculum
The Machine Learning track prepares you for applications in bioinformatics, fraud detection, intelligent systems, perception, finance and information retrieval. You’ll complete two foundational courses by selecting either two from Group A or one from each group. Group A options include Machine Learning (COMS W4771), Advanced Machine Learning (COMS W4772), Neural Networks & Deep Learning (COMS 4776) and Machine Learning Theory (COMS 4773). Group B covers Computer Vision I, Natural Language Processing, Computational Aspects of Robotics and Artificial Intelligence.
You’ll take two secondary electives beyond foundational work, with at least one at the 6000-level. Options include Advanced Database Systems, Bayesian Models in Machine Learning, Large-Scale Machine Learning, Reinforcement Learning and specialized topics in computational genomics. Technical courses at the 6000 level must account for at least 6 points. You can apply up to 3 points of Non-CS coursework if deemed sufficiently technical and relevant.
Admission Requirements
Successful applicants typically hold a GPA of 3.5 or higher, though no minimum exists. You need an undergraduate degree in computer science or a related discipline. Your degree falls outside these fields? You must complete at least four computer science courses covering foundations and programming, plus two mathematics courses. The priority deadline falls on January 15, 2026, with a regular deadline of February 15. International applicants should target a TOEFL score of 101 or IELTS score of 7. GRE scores remain optional for the 2026 admission cycle. Columbia does not defer admission.
Tuition and Cost
Tuition stands at $2,700 per point. The complete 30-credit degree totals $81,000. Additional fees include a $105 document fee (first semester only), $1,348 university services fee and $920 graduate student activities fee each year.
What Makes This Program Stand Out
Columbia offers eight specialized tracks beyond machine learning. Your interests change? The program provides flexibility. The program connects you with accomplished faculty engaged in cross-disciplinary research in augmented reality, high throughput genomics and natural language processing.
Stanford University – Master of Science in Computer Science (Artificial Intelligence Specialization)
Program Overview and Format
Stanford operates one of the most prestigious masters programs in machine learning through its on-campus MS in Computer Science with an Artificial Intelligence specialization. The terminal professional degree requires 45 units of coursework spread across a quarter system. You have three years or nine non-summer quarters to complete degree requirements, starting when your MS CS plan becomes active. The quarter system gives you flexibility in course selection and specialization pathways.
Students must enroll in at least 8 units per quarter during Autumn, Winter, and Spring terms. Summer enrollment remains optional at 0-10 units. You can reduce enrollment to as few as 3 units during your final quarter before graduation by submitting a Request for Graduate Part-Time Enrollment eForm.
Key Features and Curriculum
Your program sheet serves as a contract detailing the 45-unit requirement. You submit it before your first quarter ends to get advisor approval. The AI specialization has foundation requirements, most important implementation components, breadth courses spanning three different areas, and AI depth coursework.
You must take depth courses for letter grades with 3 or more units. A maximum of 6 units of independent study can count toward depth requirements. Sample classes are CS 221 (AI Principles & Techniques), CS 224N (Natural Language Processing with Deep Learning), and CS 229 (Machine Learning). You need at least 36 units of your degree for letter grades, and this total must have all breadth and depth courses. You must maintain a minimum 3.0 GPA.
Admission Requirements
You need a bachelor’s degree from an accredited institution, though a CS major isn’t required. Competitive applicants present a GPA of 3.7 out of 4.0. Most admitted students hold 3.5 or higher. Indian students need 70%+ or 7.0+ CGPA from recognized universities. The department requires strong quantitative and analytical skills. GRE scores are optional and not part of MS applicant evaluation. International students must submit TOEFL or IELTS scores. Your application has a two-page statement of purpose and three letters of recommendation. The application fee is $125.
Tuition and Cost
Tuition costs $21,180 per quarter for the 2025-2026 academic year. Total attendance expenses range from $130,000 to $150,000. This total covers tuition, housing, meals, books, and personal expenses.
What Makes This Program Stand Out
Stanford’s CS department ranks 2nd globally for Computer Science. It was the world’s first, founded in 1965. The Silicon Valley location gives you direct access to tech industry leaders that are Google, Apple, Meta, Tesla, and Nvidia. Graduates achieve an average starting salary of $153,400. FAANG companies offer $180,000 to $250,000+ for entry-level roles.
University of California, Berkeley – Master of Engineering in IEOR (Machine Learning and Data Science)
Program Overview and Format
Berkeley’s Master of Engineering in IEOR takes a distinct approach to machine learning education by integrating it with industrial engineering and operations research principles. The one-year full-time program combines business-oriented coursework with applications-focused IEOR courses. The program focuses on optimization analytics, risk modeling, simulation and data analysis. You can choose between two technical concentrations: Management Science & Engineering or FinTech. The program begins only in Fall term.
Key Features and Curriculum
You’ll complete core leadership courses covering marketing, finance, law, analysis and project management among technical requirements. All students must take INDENG 240 (Optimization Analytics) and INDENG 241 (Risk Modeling, Simulation, and Data Analysis). You’ll also take two additional IEOR electives in areas like data science, financial engineering or supply chain management.
The departmental Comprehensive Technical Examination is a required milestone you must pass. This three-hour written exam happens during RRR week of Fall semester. It contains two 90-minute sections: Optimization (based on INDENG 240 material that focuses on linear, integer and nonlinear programming) and Stochastic Modeling (based on INDENG 241 that covers probability theory and stochastic processes).
Admission Requirements
Applications close Wednesday, January 7, 2026 at 8:59pm PST. The application process runs electronically. Do not mail documents as they won’t be considered.
Tuition and Cost
Total tuition and fees for 2025-26 amount to $58,576.50 for California residents and $71,435.50 for non-residents. These figures include MEng tuition ($50,446.50/$63,305.50), student health insurance ($7,848) and institutional resilience fee ($282).
What Makes This Program Stand Out
Students form interdisciplinary teams and partner with industry leaders while creating real-life projects. The program’s Bay Area location provides unique advantages. The program ranks #3 nationally.
New York University – Online MS in Emerging Technologies (Machine Learning & AI)
Program Overview and Format
NYU Tandon’s Emerging Technologies program stands out among machine learning masters degree online options by letting you design a customized curriculum in nine concentrations. The 30-credit program takes 12 months to complete full-time, though part-time study extends completion to 2-3 years. You can take courses both online and on-campus. Apply as either format but choose whichever modality suits most of your classes.
Key Features and Curriculum
Your degree splits into three components: 6 credits of required applied AI courses, 12 credits of concentration coursework that has a capstone, and 12 credits of interdisciplinary electives. The Machine Learning & AI concentration lets you select three courses from options that have Machine Learning and Data Science for Bioinformatics, Artificial Intelligence I, Computer Vision, Deep Learning, and Algorithmic Machine Learning. Your capstone choice has either Advanced Machine Learning or Artificial Intelligence for Games. You can draw electives from over 50 offerings across departments and create cross-disciplinary combinations in areas like cybersecurity, robotics, or accessible experience design.
Admission Requirements
You need a four-year bachelor’s degree from an accredited institution with a minimum 3.0 GPA. GRE scores remain optional, though competitive scores strengthen applications with weaker elements. International applicants must submit TOEFL scores of 90 or IELTS scores of 7.0. Your application requires a personal essay, resume, official transcripts, and two recommendations, with a $90 application fee.
Tuition and Cost
Annual tuition stands at $43,704. Industry partners receive a 20% scholarship.
What Makes This Program Stand Out
You’ll work one-on-one with a dedicated advisor who shapes your academic plan around your interests. The flexibility extends beyond course selection: 95% of students enrolled in AI-related courses across all concentrations during the program’s first cohort.
Purdue University – Online Master of Science in Artificial Intelligence (AI and Machine Learning)
Program Overview and Format
Purdue University distinguishes its approach among masters programs in machine learning by offering two separate majors within one degree framework. The 100% online Master of Science in Artificial Intelligence features tracks for AI builders (scientists and technologists) and AI translators (business leaders and policymakers). Both just need 30 credit hours and can be completed in a year and a half when averaging six credit hours per semester. Summer courses accelerate completion.
Key Features and Curriculum
Both tracks share foundational coursework in AI ethics, policy and societal implications. AI builders take additional classes in machine learning and data science. AI translators focus on applications in business, nonprofit and public sectors along with data management and communication. All students complete a capstone course applicable to workplace projects. The curriculum draws from internationally recognized faculty who teach on Purdue’s flagship campus. You can customize your degree through interdisciplinary electives in leadership, change management and project management.
Admission Requirements
Requirements vary by major. The AI and Machine Learning track needs programming experience in Python, Data Science or Computer Science, plus prior coursework in algorithms, calculus, linear algebra and probability theory. The AI Management and Policy track just needs at least 24 months of work experience. Both just need a 3.0 cumulative GPA from an accredited institution. The program waives application fees. GRE and GMAT scores remain optional. Application deadlines fall on April 1 for summer, August 1 for fall and December 1 for spring.
Tuition and Cost
Total program cost reaches approximately $28,000.
What Makes This Program Stand Out
Purdue’s AI microcredentials earned recognition as the first courses certified by ABET. The master’s program received shortlisting for the QS Reimagining Education Awards.
Duke University – Online Master of Engineering Management (Data Analytics & Machine Learning)
Program Overview and Format
Duke MEM Online blends engineering management training with technical depth through a flexible structure designed for working professionals. The program spans two years and requires three week-long residencies at Duke’s Durham campus. You can extend completion beyond two years with approval. The format ranks #4 nationally among online engineering management programs.
Key Features and Curriculum
You’ll complete four core management courses covering marketing, IP law, finance and management, plus four technical electives that line up with your goals. The Data Analytics & Machine Learning track offers courses including Fundamentals of Data Science, Machine Learning Principles and Applications, Big Data opportunities and Data Visualization for Engineering Managers. Students take two courses per semester.
Admission Requirements
Applications require three industry or professional recommendations with at least one from a work supervisor. You’ll submit a resume, video introduction responding to a timed prompt (maximum 3 minutes) and transcripts. Duolingo serves as the preferred English proficiency test. GRE scores remain optional for 2026 applicants. The application fee costs $75, though waivers apply for veterans and current Duke students among other eligible groups.
Tuition and Cost
Tuition runs $2,900 per unit, totaling $69,600 for eight required courses. Additional costs include a $120 transcript fee and $4,500 residency fee ($1,500 per residency). Total program cost reaches $74,880.
What Makes This Program Stand Out
Graduates earn an average starting salary of $110,000 at employers including Microsoft, NVIDIA and EY. The program maintains small cohorts and offers co-op options extending up to six months.
Boston University – Online MS in Applied Data Analytics (AI & Machine Learning)
Program Overview and Format
Boston University Metropolitan College ranks its MS in Applied Data Analytics with AI & Machine Learning concentration as the #2 Best Online Master’s in Data Analytics of 2026 by TechGuide. You can study online or on campus in Boston and complete 32-40 units depending on foundation course exemptions. The program takes 8-20 months to finish and carries STEM designation.
Key Features and Curriculum
You’ll complete 10 courses total, reduced to 8 courses if exempted from foundations. Required concentration courses include Artificial Intelligence, Deep Reinforcement Learning, Advanced Machine Learning and Neural Networks, AI and Cybersecurity, Generative AI, and Computer Vision in AI. Students with 3.7+ GPA who complete four courses can pursue an optional thesis.
Admission Requirements
You need a bachelor’s degree from any discipline at a regionally accredited institution. Students lacking IT, computer science, or mathematics backgrounds may complete complimentary preparatory labs. The program waives GRE and GMAT requirements.
Tuition and Cost
Part-time students pay $567-$1,005 per unit plus $75 semester fees, totaling $27,204-$31,815 for the degree. Full-time enrollment costs $34,935 per semester with $501 fees.
What Makes This Program Stand Out
You’ll benefit from a 24:1 student-to-instructor ratio and automatic merit scholarship consideration during admission. Graduate Melissa Viator secured a data scientist position at Massachusetts General Hospital and implemented machine learning models to improve operations.
Stevens Institute of Technology – Online Master of Science in Machine Learning
Program Overview and Format
Stevens Institute of Technology positions its machine learning masters degree online in the heart of the New York City metropolitan area, where over 7,500 tech companies hire graduates. You can complete the 30 graduate credits in 18 to 24 months while studying online.
Key Features and Curriculum
The curriculum requires five core courses covering Artificial Intelligence, deep learning and natural language processing, plus three elective courses. Courses emphasize theoretical analysis and practical implementation in machine learning. You can complete a thesis with faculty members if you choose.
Admission Requirements
Stevens waives GRE and GMAT requirements. You’ll submit two letters of recommendation, a statement of purpose, official transcripts and a $60 application fee. International students must achieve TOEFL scores of 80+ or IELTS 6.5+.
Tuition and Cost
First-year tuition totals $43,528. Students should budget an additional $17,900 to cover living expenses.
What Makes This Program Stand Out
Stevens ranks among the top 25 nationally in Best Online Graduate Information Technology Programs in 2026. Graduates achieve 89% employment within six months and the program average salary reaches $121,000. Alumni secure positions at Amazon, Google, Facebook and IBM.
Drexel University – Online Master of Science in Artificial Intelligence and Machine Learning
Program Overview and Format
Drexel structures its interdisciplinary MS around three focus areas: data science and analytics, theory of computation and algorithms, and applications of artificial intelligence and machine learning. The 45-quarter credit program operates online or on-campus and takes 2-3 years full-time or 2-4 years part-time to complete. Drexel runs on a quarter system with four 10-week terms annually. You can take more courses in shorter periods compared to traditional semester formats.
Key Features and Curriculum
You’ll choose between Applied and Computational concentrations. The Applied track suits professionals without computer science backgrounds and focuses on selecting appropriate algorithms and maintaining AI codebases. The Computational concentration targets those with technical backgrounds interested in developing original algorithms and learning mathematical foundations. Your 9 core credits cover programming foundations, machine learning applications, and applied AI. You’ll select 15 credits from major electives spanning data science foundations, AI foundations, and human-centered computing, plus 15 flexible elective credits. The program concludes with a two-term capstone that addresses real-life problems.
Admission Requirements
Requirements depend on your chosen concentration. Students lacking computer science degrees can enter the Applied concentration or complete Drexel’s Graduate Certificate in Computer Science as an entry point. You need a four-year bachelor’s degree from a regionally accredited institution. International applicants must achieve TOEFL scores of 90, IELTS 6.5, PTE 61, or Duolingo 110. The application has a 500-word essay, resume, official transcripts, and one required recommendation (two preferred), with a $65 application fee.
Tuition and Cost
Online students pay $1,481 per credit plus a $125 annual program fee for academic year 2025-2026. Total program cost reaches approximately $66,770.
What Makes This Program Stand Out
Faculty maintain active research in machine learning, computer vision, and cognitive science. Full-time on-campus students can pursue graduate co-op opportunities to gain hands-on industry experience.
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Finding Programs
With these points in mind, selecting the right program depends on your specific circumstances. Budget-conscious professionals might gravitate toward Georgia Tech’s $9,030 option. Those seeking prestige could think over Stanford or Carnegie Mellon despite higher costs. Your technical background matters just as much: programs like Drexel and NYU welcome non-CS graduates. Stanford and Carnegie Mellon prefer stronger technical foundations.
Start by evaluating your budget constraints and preferred learning format (online versus on-campus). Then narrow your choices based on how the curriculum matches your career goals. Each program delivers distinct advantages, so the best fit reflects your individual priorities rather than rankings alone.