The 12 Best Online Masters Machine Learning Programs in 2026 (& How to Choose)
An online masters machine learning degree doesn’t have to drain your savings. Georgia Tech’s program, for example, costs under $9,000 in total. But affordability is just one factor to think over.
Machine learning specialists are in high need in industries of all types. An MS in machine learning online offers the flexibility to advance your career while working. These programs cover computer vision, natural language processing, and robotics applications.
In this piece we get into 12 top online masters in machine learning programs and help you choose the right one for your goals.
Georgia Institute of Technology – Online MSCS with Machine Learning Specialization
Program Overview and Format
Georgia Tech’s Online Master of Science in Computer Science (OMSCS) with Machine Learning specialization delivers all coursework asynchronously. You watch lectures and complete assignments on your own schedule, letting you balance work and study. The program lets you enroll in one course per semester and grants up to six years to complete the degree.
This structure works for professionals who just need flexibility. You’re not locked into a rigid timeline, and the asynchronous format means no scheduled class meetings.
Curriculum Structure
The degree just needs 30 credit hours, equivalent to 10 courses. You complete a 15-hour machine learning specialization as part of this total. The specialization just needs two core courses: one algorithms course (such as CS 6515 Introduction to Graduate Algorithms) and one machine learning course (CS 7641 Machine Learning or CSE 6740 Computational Data Analysis). After these cores, you select three electives totaling 9 hours from ML-focused options.
Elective choices include CS 7642 Reinforcement Learning and Decision Making, CS 7643 Deep Learning, CS 7646 Machine Learning for Trading, CS 6476 Computer Vision, and CSE 6242 Data and Visual Analytics. Each elective must have at least one-third of its graded content based on machine learning. The remaining 15 credit hours are free electives, which can be any OMSCS courses.
Grade requirements vary by course type. Specialization courses just need a B or higher, while other courses just need a C minimum. You must maintain a 3.0 cumulative GPA to graduate.
Tuition and Affordability
Tuition runs $180 per credit hour. You also pay a $107 technology fee each semester. The complete 30-credit program costs around $7,000 in total. This price point makes Georgia Tech one of the most affordable options for an online masters in machine learning.
Financial aid applies to OMSCS students, and many employers cover the entire cost through tuition reimbursement programs given the modest total.
What Makes Georgia Tech Stand Out
The program graduated over 10,000 students in its first decade and enrolls more than 12,000 now. Forbes called it “the greatest degree program ever” because it combines top-tier reputation with disruptive pricing. Georgia Tech ranks among the most employer-connected universities, with strong industry arrangement in any discipline.
University of Washington – MS in AIML for Engineering
Program Overview and Format
University of Washington structures its MS in AIML for Engineering as a stacked credential program. You start with the Graduate Certificate in AI & ML for Engineering, then add a domain-specific certificate and complete a capstone project to earn the master’s degree. This approach lets you earn credentials one at a time while working.
The program runs online with asynchronous coursework. You can complete it part-time over two to four years. This distributes costs over time and may give you access to employer funding or tax benefits between certificates. Full-time enrollment is also available.
One limitation: the program doesn’t admit F1 or J1 visa students who need I-20 or DS-2019 documentation. But students outside the United States can complete the degree online.
Curriculum Structure
The foundation certificate contains 16 credits spread across five courses. You take a 5-credit Foundations of Machine Learning for Engineering course that covers math skills, coding, AI ethics and engineering applications. This pairs with a 4-credit Data-Driven Optimization course. The course teaches convex and nonconvex optimization, constrained optimization and computational techniques for big data.
The 3-credit Physics-Informed Machine Learning course addresses algorithms for scientific problem solving. These include physics-informed neural networks, digital twins and reinforcement learning. You complete a 2-credit Machine Learning for Engineering Project where you implement end-to-end solutions. You then assess them for efficacy, accuracy, safety and ethics. The final 2 credits come from seminars or electives.
You select a domain-specific certificate that lines up with your engineering field after the foundation certificate. Then you finish with a two-quarter capstone sequence.
Applications open January 15, 2026, with a June 1st deadline for Fall 2026 admission. You need a 3.0 GPA and undergraduate coursework in calculus, differential equations, matrix algebra and physics, plus coding experience. No GRE required.
Tuition and Affordability
The foundation certificate costs about $18,000. Total degree cost ranges between $40,375 and $43,088. The final amount depends on which domain-specific certificate you choose. These rates may change in future years.
What Makes UW Stand Out
The program received development funding from The Boeing Company. Faculty include Steve Brunton, Director of the AI Center for Dynamics & Control. His work spans fluid dynamics and closed-loop turbulence control. Nathan Kutz contributes expertise in numerical methods and scientific computing across nonlinear optics and neuroscience. Michelle Hickner focuses on engineering education and data-driven system identification.
Columbia University – Online MSCS with Machine Learning Track
Program Overview and Format
Columbia’s online MS in Computer Science with Machine Learning track runs through the Columbia Video Network (CVN) and delivers all coursework online. The Machine Learning pathway targets professionals who seek expertise in techniques that span bioinformatics, fraud detection, intelligent systems, perception, finance and information retrieval.
You complete 30 graduate credits and maintain a minimum 2.7 GPA. The program allows up to five years to complete the degree. No GRE is required, though you need a minimum 3.3 GPA to gain admission. You select your track in MICE when you enroll and can change it until your second semester begins.
Curriculum Structure
The curriculum divides into foundational courses, secondary electives and general electives. You complete at least six points of technical courses at the 6000 level.
Foundational requirements need two courses: either both from Group A or one from Group A and one from Group B, with at least one from Group A. Group A options are COMS W4771 Machine Learning, COMS W4772 Advanced Machine Learning, COMS 4776 Neural Networks & Deep Learning, and COMS W4252 Introduction to Computational Learning Theory. Group B has COMS W4731 Computer Vision I, COMS W4705 Natural Language Processing and COMS W4701 Artificial Intelligence.
Secondary electives require two courses, with at least one at the 6000 level. Options span COMS E6232 Analysis of Algorithms II, EECS E6691 Advanced Deep Learning, ELEN 6885 Reinforcement Learning, IEOR E8100 Optimization Methods in Machine Learning and STAT 5242 Advanced Machine Learning. General electives fill remaining credits. You can take up to three points from non-CS courses if they are relevant and technical.
Tuition and Affordability
Tuition costs $2,700 per credit point for graduate engineering students. The complete 30-credit program reaches $81,000 in total tuition. Additional fees cover health insurance, student activities and university services.
What Makes Columbia Stand Out
Columbia offers eight faculty-determined pathways beyond Machine Learning. These are Computational Biology, Computer Security, Natural Language Processing and Vision and Graphics. You can also design an individual-specific pathway or pursue an MS Thesis option with faculty supervision.
Stevens Institute of Technology – Online MS in Machine Learning
Program Overview and Format
Stevens Institute of Technology offers a dedicated MS in Machine Learning rather than a specialization within computer science. This difference matters because the entire curriculum focuses on machine learning theory and applications. The program runs online and on campus, with completion taking 18 to 24 months.
You need 30 graduate credits total with a minimum 3.0 GPA and no grade below C in any course. The structure permits up to six years for completion and allows part-time enrollment while working. You can work on a thesis with faculty members as an option.
Curriculum Structure
The degree divides credits into three categories. You select four courses from five machine learning core options: CS 541 Artificial Intelligence, CS 559 Machine Learning Fundamentals and Applications, CS 560 Statistical Machine Learning, CS 583 Deep Learning, and CS 584 Natural Language Processing. These four cores consume 12 credits.
You complete three machine learning core electives totaling 9 credits from options that include CS 532 3D Computer Vision, CS 556 Mathematical Foundations of Machine Learning, CS 558 Computer Vision, CS 582 Causal Inference, BIA 662 Augmented Intelligence and Generative AI, CPE 595 Applied Machine Learning, and MA 661 Dynamic Programming and Reinforcement Learning. The remaining 9 credits come from general electives, which can be any graduate course your advisor approves.
Prerequisite requirements include undergraduate linear algebra and probability, with CS 556 Mathematical Foundations of Machine Learning available to build these skills.
Tuition and Affordability
First-year tuition costs $43,528. Besides tuition, budget around $17,900 for living expenses. Total program costs vary based on course selection and timeline.
What Makes Stevens Stand Out
Stevens ranks in the top 25 for Best Online Graduate Information Technology Programs per U.S. News and World Report 2026 rankings. Employment outcomes show 89% of graduates find positions within six months of graduation. The Class of 2023 reported a mean compensation of $121,000.
Graduates have been hired at Amazon, Bloomberg, Facebook, Google, IBM, and Intel. The program’s location in the New York City metropolitan area gives access to over 7,500 tech companies. Stevens maintains strong industry partnerships and research opportunities through state-of-the-art labs and the MakerCenter.
Purdue University – Online MSAI with AI and Machine Learning Pathway
Program Overview and Format
Purdue University splits its online Master of Science in Artificial Intelligence into two distinct majors, each serving different professional needs. The AI and Machine Learning major targets scientists and technologists who build AI systems. It requires programming expertise in Python along with coursework in algorithms, calculus, linear algebra, and probability theory. The AI Management and Policy major serves business leaders and policymakers who need to make informed AI decisions. This track requires 24 months of relevant work experience instead of technical prerequisites.
Both tracks run 100% online with flexible pacing. Students averaging six credit hours per semester complete the 30-credit program in about 18 months. The program charges no application fee.
Curriculum Structure
All students complete 10 credits of foundational courses covering interdisciplinary AI fundamentals, AI policy and governance, societal effects, and a capstone project. The capstone provides a chance to apply learning to workplace projects.
The AI and Machine Learning major adds 2 credits of advanced technical fundamentals. Students then complete 6 credits across two selective topics: one course from AI/ML options (such as Statistical Machine Learning or Natural Language Processing) and one from Data Mining courses[242]. The remaining 12 credits come from technical/professional electives and free electives with advisor approval.
Admission requires a bachelor’s degree from an accredited institution and a cumulative 3.0 GPA.
Tuition and Affordability
Purdue’s online programs use per-credit-hour pricing. Students report the program as economical compared to other state options, with one noting that “many MSAI programs in my state are cost prohibitive” while Purdue’s structure made the degree affordable.
What Makes Purdue Stand Out
The interdisciplinary design allows students to work with faculty across multiple departments and customize their curriculum to match employer needs. Students can select electives in leadership, change management, and project management alongside technical courses. Professor Cherie Maestas from the Department of Political Science emphasizes that the program prepares both technical experts and business leaders to cooperate in controlling AI.
New York University – MS in Emerging Technologies (ML & AI)
Program Overview and Format
NYU Tandon’s MS in Emerging Technologies stands apart by allowing you to design your own curriculum in nine technology concentrations. The program runs both on-campus and online, with the online format launching in 2023. You complete 30 credits with support from an advisor who helps shape your academic plan around your career goals.
The Machine Learning & AI concentration represents one of nine options, among other areas like cybersecurity, robotics, user experience design, data science, urban informatics, wireless & networking, change management and software engineering. You can switch your concentration once during the program, provided you’ve completed one semester in your original plan and aren’t in your final semester.
Curriculum Structure
The degree requires 6 credits of applied AI courses, 12 credits of concentration coursework including a capstone, and 12 credits of interdisciplinary electives. For the ML & AI concentration, you select three courses totaling 9 credits from options including Machine Learning and Data Science for Bioinformatics, Design and Analysis of Algorithms, Artificial Intelligence, Computer Vision, Algorithmic Machine Learning and Data Science, or Deep Learning.
Your capstone involves either ECE-GY 7143 Advanced Machine Learning, where you propose and assess new deep learning methods, or CS-GY 6943 Artificial Intelligence for Games, producing publishable research. The 12 elective credits can come from any of the nine concentration areas or from schools outside Tandon.
Tuition and Affordability
Annual tuition costs approximately $75,750. Financial aid options include merit scholarships reviewed automatically upon admission, with awards based on academic performance.
What Makes NYU Stand Out
Early data shows that 95% of students in all concentrations enrolled in AI-related courses during the program’s first cohort. This interdisciplinary demand confirms the program’s approach to integrating AI in multiple disciplines rather than isolating it within computer science.
Duke University – Online MEM with Data Analytics & Machine Learning
Program Overview and Format
Duke’s Master of Engineering Management is different from traditional online masters in machine learning by emphasizing business leadership among technical depth. The online program combines four core management courses developed with Duke Law School and Fuqua School of Business with four technical electives. You can specialize in Data Analytics and Machine Learning through one of six available elective tracks.
The program requires three week-long residencies at Duke throughout your studies. Most online programs operate remotely, but these on-campus sessions provide face-to-face collaboration opportunities. You complete the degree in two years, taking two courses per semester. Students can extend the program to three or four years with advisor approval on a case-by-case basis.
Curriculum Structure
Core management courses cover Marketing (EGRMGMT 510), IP Law (EGRMGMT 520), Finance (EGRMGMT 530), and Management (EGRMGMT 540). Technical electives for the Data Analytics and Machine Learning track include EGRMGMT 585 Fundamentals of Data Science, EGRMGMT 586 New Opportunities in Big Data, EGRMGMT 587 Data Visualization, and EGRMGMT 588 Machine Learning Principles and Applications.
You complete a capstone experience during your final residency (EGRMGMT 550/551). Students can switch between elective tracks or build custom combinations to match their specific career objectives.
Tuition and Affordability
Total tuition costs $72,300 for the 30-credit program, charged at $2,410 per credit hour. You pay around $14,460 per semester when taking two courses. Budget an additional $120 transcript fee and $660 for books. Internship and residency courses don’t incur tuition charges, though residencies include room and board fees.
What Makes Duke Stand Out
Nine out of ten graduates secure employment or continue education within six months of graduation. Starting salaries for 2022 graduates averaged $110,000 at employers including Microsoft, EY, and NVIDIA.
University of Illinois Chicago – Online MEng in AI and Machine Learning
Program Overview and Format
UIC’s Master of Engineering with a concentration in AI and Machine Learning operates as a professional, non-thesis degree. The program targets working engineers, scientists and technical professionals. You complete 9 courses totaling 36 credit hours. All courses are delivered 100% online through asynchronous instruction. The accelerated 8-week term structure allows full-time students to finish in as few as 12 months. Part-time students can extend the timeline to fit their schedules.
This program is different from research-focused degrees. It emphasizes applied skills among leadership development. Full-time enrollment involves two 8-week courses at once, and part-time students complete one course per term.
Curriculum Structure
The 9-course curriculum splits between technical AI/ML training and business leadership components. Four courses focus on AI and machine learning fundamentals. These cover neural networks, natural language processing and deep neural networks for different applications. Specific offerings include MENG 419 Introduction to Artificial Intelligence, which exposes you to AI tools relevant to career challenges.
Leadership-focused credits address innovation tools and methods. Engineering management comes through courses like MENG 401 Engineering Management. Engineering law fundamentals come via MENG 400. The engineering management course teaches you to oversee project lifecycle elements. These include scope, cost, time, risk and quality. Engineering law coursework emphasizes ethics, fairness and bias considerations in AI development.
Tuition and Affordability
Total program cost stands at $32,256. This positions it well below average master’s degree tuition. Library and technology fees add $21 per credit hour beyond base tuition. UIC offers pay-by-course payment options. You pay only for courses you need. Financial aid applicants should file FAFSA using UIC’s Federal School Code 001776.
What Makes UIC Stand Out
MastersInAI.org ranked the program #9 for 2025. The ranking highlights its affordability and engineering management integration. UIC is a Carnegie R1 institution that conducts research at the highest levels. The computer science department maintains Natural Language Processing and Machine Learning laboratories.
Rice University – Online MDS with Machine Learning Track
Program Overview and Format
Rice University’s online Master of Data Science offers machine learning as one of three specialization tracks among business analytics and image processing. The program runs online with asynchronous coursework and allows you to balance full-time employment with your studies. Most working professionals complete the degree in 2.5 to 3 years and take one or two courses per term. You have up to five years to complete the program. Three start dates are offered annually in fall and spring.
The structure suits those without computer science backgrounds. Core courses cover computational and programming fundamentals before advancing to specialized topics.
Curriculum Structure
You complete a minimum of 31 credit hours. Five core courses are the foundations in Python programming, machine learning algorithms, data visualization and statistical analysis. The machine learning specialization requires 9 credits across three courses: Natural Language Processing, Statistical Machine Learning, and Deep Learning. A 4-credit capstone project applies your skills to real-life datasets that industry clients sponsor.
Tuition and Affordability
Tuition costs $1,666.70 per credit hour. Total program cost reaches about $51,000 for 31 credits. Applicants who submit early applications qualify for $10,000 merit-based scholarships.
What Makes Rice Stand Out
The interdisciplinary design accepts students from non-technical backgrounds and makes data science available in a variety of industries. Applicants with a 3.0+ GPA face no GRE requirement.
Boston University – Online MS in Applied Data Analytics (AI & ML)
Program Overview and Format
Boston University’s MS in Applied Data Analytics offers an AI & Machine Learning concentration that provides in-depth study of neural networks, generative AI, automated reasoning, AI security, intelligent image processing, and reinforcement learning among other ethical AI considerations. You can complete the degree online or on campus with part-time or full-time enrollment options. The online program provides six start dates each year.
The program requires 10 courses totaling 40 units, though students with appropriate backgrounds may receive waivers for up to two foundation courses. This reduces requirements to 8 courses and 32 units. Foundation courses, when assigned, must be completed within your first semester. Students with a GPA of 3.7 or higher after completing four courses can pursue an optional thesis.
Curriculum Structure
You complete foundation courses (unless exempted), core courses covering data analytics fundamentals, and AI & Machine Learning concentration requirements. The curriculum immerses you in organizing and analyzing large datasets while teaching you to visualize them using current industry tools. You learn about database systems and data mining tools. The program also covers Python and R packages along with cloud services.
Tuition and Affordability
Part-time students pay $567 to $1,005 per unit, with total degree costs ranging from $27,204 to $31,815. Full-time enrollment costs $34,935 per semester with additional fees of $501. All admitted students are considered for merit scholarships.
What Makes BU Stand Out
TechGuide ranks the program #2 among Best Online Master’s in Data Analytics programs for 2026. U.S. News ranks BU’s online computer information technology programs #12 nationwide. You benefit from a 24:1 student-to-instructor ratio[452] and STEM designation providing OPT extensions for international graduates.
University of New Mexico – Online MSCE in Applied ML & AI
Program Overview and Format
Google and Sandia National Laboratories co-designed UNM’s MS in Computer Engineering with Applied ML & AI concentration. The coursework-only program delivers content through eight and 16-week online formats. You complete 31 credit hours in 18 months or more, with no application deadlines and rolling admission year-round.
Curriculum Structure
Required courses span 13-16 credits: ECE 517 Machine Learning, ECE 510 Deep Learning, ECE 533 Digital Image Processing, ECE 590 Graduate Seminar (1 credit), and ECE 551 Problems to focus on ML-based projects (3-6 credits). Electives provide the remaining 15-18 credits and include optimization theory, AI infrastructure, advanced networking, cloud computing, and IoT. Faculty advisors work one-to-one with you on your ML project.
Tuition and Affordability
Total program cost reaches $16,701. Tuition runs $538.72 per credit hour. This combines $432.40 base tuition with a $106.32 School of Engineering differential. You pay a $180 student technology fee each fall and spring semester.
What Makes UNM Stand Out
Faculty include Google Principal Engineer Ioannis Papapanagiotou teaching AI infrastructure and Sandia cybersecurity scientist Christopher Lamb. UNM holds Carnegie R1 status and founded the New Mexico Artificial Intelligence Consortium. The university keeps direct partnerships with Los Alamos and Sandia National Laboratories.
Drexel University – Online MSAIML
Program Overview and Format
Drexel’s MS in Artificial Intelligence and Machine Learning operates on a quarter system with four 10-week terms annually. This allows more frequent course starts and accelerated progress. You can complete the 45 quarter credits (equivalent to 30 semester credits) online or on-campus in 2-3 years full-time or 2-4 years part-time.
The program offers Applied and Computational tracks. The Applied track suits professionals without strong computer science backgrounds and requires CS 501 Introduction to Programming or CS 570 Programming Foundations. The Computational track targets those with stronger technical foundations and requires CS 510 Introduction to Artificial Intelligence, CS 613 Machine Learning, and CS 615 Deep Learning.
Curriculum Structure
You complete 5 core courses and 5 major-specific electives (with at least one from each designated group). You also take 5 flexible electives. The program ends in a two-term capstone where you tackle real-life or research problems.
You can select up to three integrated certificates while earning your degree. Options include Applied AI and ML, Big Data Analytics, and Data Science Foundations. These stackable credentials provide incremental validation of your skills.
Tuition and Affordability
Tuition costs $1,438 per credit. Total program cost reaches $64,710 before financial aid. Drexel offers reduced rates for alumni and military-affiliated students.
What Makes Drexel Stand Out
Full-time on-campus students access co-op placements through the Steinbright Career Development Center. They apply skills in paid positions before graduation.
How to Choose the Best Online Masters Machine Learning Program for You
Review Your Career Goals and Background
Determine whether you want to build AI systems or apply machine learning within organizational contexts. Programs accept around 40% of students without related degrees, but you’ll need strong foundations in calculus, linear algebra, probability and programming to succeed. Technical roles like ML engineer require deeper mathematical preparation. Applied positions emphasize deployment skills.
Think About Program Type and Specialization Focus
Standalone MS in machine learning programs like Stevens dedicate all coursework to ML theory and applications. Specializations within computer science degrees offer broader computing exposure with ML focus areas. Your choice depends on whether you want narrow depth or breadth across disciplines.
Review Cost vs. Value and ROI
Total costs range from $7,000 to $81,000 across programs. Financial aid assists 85% of graduate students. Employer perception matters: 75% of companies view online degrees as credible as campus programs. Calculate payback period based on expected salary increases in your target role.
Check Accreditation and University Reputation
Regional accreditation will give employer recognition, with 61% of HR leaders preferring degrees from credible sources. University prestige affects opportunities at first. Skills drive long-term advancement though.
Review Curriculum Flexibility and Elective Options
Get into whether programs offer elective depth matching your specialization interests. Some restrict online students from certain advanced courses, so verify availability before enrolling.
Get Into Time Commitment and Program Length
Full-time online masters in machine learning require 18-24 months. Part-time enrollment extends to 3-5 years. Self-paced options appeal to 72% of online learners and balance work commitments with academic progress.
Conclusion
By and large, selecting the right online masters in machine learning program depends on your specific career goals, budget, and technical background. Programs range from Georgia Tech’s $7,000 option to Columbia’s $81,000 offering, each with distinct advantages.
You should review curriculum depth, accreditation status, and career outcomes before committing. Think over whether you need a standalone ML degree or a computer science specialization with ML focus. In fact, the best program matches your professional objectives while fitting your financial constraints and timeline.
Shortlist three programs that match your priorities first. Then contact admissions advisors for detailed curriculum breakdowns and employment statistics.