What Makes an Online Master’s in Machine Learning Program Elite?

The best online master’s in machine learning programs tend to have very specific characteristics:

7 Reasons to Consider a Master’s in Machine Learning Degree Online

An online master’s in ML degree is an ideal credential for professionals who want to break into the AI/ML industry. It’s also a good way for non-tech majors to more thoroughly understand the ML systems they’re already using in their work. With the flexibility online programs offer, you can continue your full-time job while building the academic foundation and practical skills you need to pursue a career in machine learning or artificial intelligence.

Here are the top seven reasons to pursue an online master’s degree in machine learning.

1. You’ll satisfy a required credential for AI/ML roles. Many of today’s Big Tech roles (especially research-oriented, specialized, and senior technical roles) require formal education in AI/ML. While you may be able to fulfill this requirement with a bachelor’s degree in an area like computer science or computer engineering, having a dedicated degree in ML puts you ahead of applicants who don’t have that level of education. It can also result in higher pay. An analysis from PwC reported that workers with these advanced skills command a 62% wage premium.

You’ll also have more practical experience with the tools and workflows used in these roles, such as Python, Pandas, Scikit-learn, and MLOps.

This job description for a software engineer with Meta is just one example. They prefer applicants with a master’s degree and experience in TensorFlow, PyTorch, and Scikit-learn.

2. You can use a master’s degree in ML to switch careers. If you’ve spent several years working in software development or data science, you might be ready to move on to something new. You most likely already have the foundation needed for a career in ML. But getting a master’s degree in ML will help you develop the specific technical knowledge you need to step into a new role.

You’ll expand your career opportunities and have the potential to work as an ML engineer, NLP specialist, or computer vision engineer. The number of jobs in these fields is growing rapidly. For instance, the Bureau of Labor Statistics says the number of data scientist jobs is expected to grow by 35% within the next decade.

3. You’ll gain the technical knowledge you need to support business-focused ML deployments. Since AI/ML is such a new field, many business professionals are being tasked with deploying ML models and systems without understanding how they function from a technical standpoint. A master’s degree in ML will teach you the theoretical concepts behind ML and give you hands-on experience working through the entire ML workflow. In addition, many programs also take a close look at some legal and social implications that could impact the ML projects you’re building on the job.

Purdue’s M.S. in Artificial Intelligence with a specialization in Machine Learning is one example. It requires all students to take courses in Artificial Intelligence Policy, Governance, and Ethics as well as Societal Impacts of Artificial Intelligence.

4. You will get several opportunities to build your AI/ML portfolio. If you have a bachelor’s degree in a technical field, you likely already have a project or two in your portfolio. Working through a master’s degree in ML gives you the chance to expand your portfolio and expressly prove your practical abilities in ML. Most programs offer some experience with real-world datasets and challenges. If you choose a program from an R1 institution, you may be able to work alongside industry-leading researchers.

On the other hand, some programs connect students with businesses and organizations, giving them a way to see how ML projects can deliver real business value. Boston University does this through its two-semester AI in Industry Series. The university invites AI/ML industry experts to speak to the class and work through case studies, so the students can practice applying their knowledge to real-world professional challenges.

5. You can keep your current career and income. With an online master’s program, you can stay where you are and keep your full-time job and salary. This also means you can immediately apply what you’re learning in your ML courses to your current role. In fact, many online master’s in ML programs are designed specifically for professionals who are working full-time.

SMU’s program, for example, blends live lectures with independent learning opportunities so you don’t have to choose between your job and your degree. Plus, many programs have extended, flexible pathways that allow you to take up to 3-5 years to complete your degree. The University of Washington – Seattle offers even more time, up to six years to finish the courses and a capstone project.

6. Online master’s in ML programs provide more options and flexibility. In-person master’s degrees typically require working professionals to attend classes for a few hours in the evening. If you have a family or other after-work responsibilities, it’s nearly impossible to attend a program like this.

Many online master’s programs offer a blend of live and recorded lectures so you get a balance of structure and freedom. Others are totally asynchronous, giving you complete control in setting your own schedule. For example, at both ODU and UNM, courses last just eight weeks and have no live sessions. That means you don’t have to miss important family or work events in order to make it to class.

7. Online ML master’s programs can be really affordable. In some cases, tuition for online master’s degree programs is cheaper than in-person options. The average cost for the programs on our list is about $35,500, which is way below the nationwide average for a master’s degree ($62,820). In fact, Georgia Tech’s program comes in as a major budget-saver at just under $7K.

However, even if tuition costs are comparable, online options save you the costs of moving, daily commuting, and in-person student fees. This is especially relevant if you’re wanting to attend a program that’s headquartered in a big city, like Columbia or Boston University. Plus, by staying where you’re at, you can continue working full-time, and your employer may even pay a portion of your tuition.

Best Online Master’s in Machine Learning Programs In 2027

1

Georgia Institute of Technology

ATLANTA, GA

Overview

M.S. in Computer Science (OMSCS) – Machine Learning specialization

Georgia Tech’s online M.S. in Computer Science (OMSCS) with a Machine Learning specialization will give you a solid technical education at an incredibly affordable price. You can pick from more than 75 course options that cover advanced, technical ML coursework and a wide range of electives. It’s designed for working professionals who need flexibility, so you can register for one to three courses per semester and take as long as six years to complete the degree.

  • Top Pick For: Affordability; Variety of Electives
  • Estimated Tuition: $6,750
  • Typical Length: 2–4 years
  • Accreditation: SACSCOC
  • AI/ML Specific Credits: 15
  • Total Credits: 30

Why Study ML at Georgia Tech?

Georgia Tech’s OMSCS program takes the top spot in our rankings because no other program offers a better price. It’s about $6K cheaper than the next-lowest option (#13 WGU). The low tuition isn’t indicative of a bare-bones degree, though. The program has a 12-year track record, which translates to a thorough course catalog and a large alumni network. About 2,500 students graduate each year.

OMSCS is consistently recognized for its academic quality. Georgia Tech comes in seventh in the 2026 U.S. News and World Report’s list of Best Computer Science Schools, and it ranks fifth in the AI specialty rankings.

You’ll get direct access to that top-tier curriculum with 15 credits specifically devoted to ML. Two classes (Machine Learning and Introduction to Graduate Algorithms) are required, but the rest of your hours can come from the courses you choose. Electives, like Computer Vision, Network Science, and Machine Learning for Trading, give you plenty of room to explore your interests. If you want to do a thesis or capstone, though, you’ll need to look at schools like Georgia Southern University or ODU instead.

Once you finish the program, you’re likely to earn a six-figure salary. Georgia Tech reports that the median starting salary of OMSCS graduates is $138,500.

Here’s how one student on Reddit summed up OMSCS. “They’ve managed to create an incredible academic program for a completely affordable cost. It takes a lot of discipline to buckle down and get through it.”

LEARN MORE >
2

University of New Mexico

ALBUQUERQUE, NM

Overview

M.S. in Computer Engineering – Machine Learning & AI Concentration

You can complete UNM’s accelerated M.S. in Computer Engineering with a concentration in Applied Machine Learning and Artificial Intelligence Systems Engineering in as little as 18 months. Technical-minded students who want to upskill quickly are likely to get the most value out of the degree. The program doesn’t specify certain B.S. majors as a prerequisite, but the university does recommend you have experience in undergrad classes like statistics, linear algebra, and computer programming.

  • Top Pick For: Affordability; Professionals with a B.S. in Computer Engineering
  • Estimated Tuition: $16,700
  • Typical Length: 18 months
  • Accreditation: HLC
  • AI/ML Specific Credits: 13–16
  • Total Credits: 31

Why Study ML at UNM?

UNM’s program provides a structured, highly technical approach to machine learning at a great price. (It’s the third most affordable option on our list.) It’s also a great fit if you’re looking to get your master’s degree fast. Some of the courses are offered through an eight-week accelerated structure, much like ODU and UIC.

You’ll have the chance to take a considerable amount of electives, about 16 hours. While UNM’s list of electives only includes 13 courses, they go into niche engineering topics like Electrodynamics and Hardware Software Codesign with FPGAs. There’s also a research requirement called “Problems” that allows you to work one-on-one with a faculty member without needing to commit to a program with a thesis track.

An added bonus for networking connections: many of these classes are taught by experts. Dr. Ioannis Papapanagiotou is a principal engineer with experience at Google and Netflix, and Dr. Don Hush has worked at the Sandia National Laboratories and the Los Alamos National Laboratory.

LEARN MORE >
3

University of Washington–Seattle

SEATTLE, WA

Overview

M.S. in Artificial Intelligence & Machine Learning for Engineering

The University of Washington’s College of Engineering introduced a new online format for its master’s degree in the spring of 2025. If you’re uncertain about which direction you’d like your degree to take, or if you need an extended timeline, this program offers options. Its modular structure provides several tracks that all end with a M.S. in Artificial Intelligence and Machine Learning for Engineering.

  • Top Pick For: Flexibility; Slow Paced; Customized Degree
  • Estimated Tuition: $43,088 (Data-Driven Dynamic Systems and Controls for Engineering)
  • Typical Length: 1.5–4 years
  • Accreditation: NWCCU
  • AI/ML Specific Credits: 28–29
  • Total Credits: 39–42

Why Study ML at UW?

UW’s stackable, modular method gives you the ultimate flexibility and customization in your education. It’s also the top-ranking named degree on the list, which points to its focus on advanced ML curriculum and research. The program is application-focused, leaning into specific domains like robotics, chemical processes, and manufacturing.

Everybody starts with a 16-credit Graduate Certificate in AI & Machine Learning for Engineering that covers advanced studies in math and physics, AI/ML topics, and project-based experiences. After that, you have three certificate options, which let you personally shape your degree around your goals. You can choose from Data-Driven Dynamic Systems and Control for Engineering, Data Analytics for Systems Operations, or AI for Materials Engineering.

Because you can take up to six years to finish, it’s an ideal program for busy professionals. Georgia Tech is the only other program on our list that gives this much time.

LEARN MORE >
4

Rice University

HOUSTON, TX

Overview

Master of Data Science (Online) – Machine Learning specialization

You’ll get some flexibility along with a week-by-week structure in Rice University’s program for an M.D.S. with a specialization in AI/ML. While the program is fully online, you are required to attend weekly live sessions. The program’s curriculum provides a broad overview of the technical elements of ML with Python, statistics, and big data in addition to five niche AI/ML courses.

  • Top Pick For: Data-Focused Courses; Live Online Sessions; Industry Experience
  • Estimated Tuition: $52,700
  • Typical Length: 2 years
  • Accreditation: SACSCOC
  • AI/ML Specific Credits: 24
  • Total Credits: 31

Why Study ML at Rice?

Over the last eight years, Rice has dedicated $45M to expand its data science program and its application to AI/ML. The school is gaining recognition among outside organizations too. It recently received a $20M award from the National Science Foundation to use AI to advance the development of electronic and quantum materials.

This investment shows up throughout the program for the M.S. in Data Science. You’ll get a wide view of the ML technical workflow and the opportunity to demonstrate those technical skills through a team capstone project in Rice’s D2K Lab, the Data-to-Knowledge Lab. You’ll be paired with companies from the community and apply your skills to execute a data science pipeline from beginning to end. This is a great match for you if you want an industry-specific applied experience instead of a purely academic program (like Columbia) or a substantial thesis track (like Georgia Southern).

But if you prefer a low-cost asynchronous program, look elsewhere. Rice costs 3x more than UNM and 7x more than Georgia Tech, plus it requires weekly live attendance.

LEARN MORE >
5

Stevens Institute of Technology

HOBOKEN, NJ

Overview

M.S. in Machine Learning

The M.S. in Machine Learning degree from Stevens Institute of Technology provides a very ML-heavy course sequence, but that shouldn’t scare away students with low undergraduate GPAs or GRE scores. Stevens doesn’t have requirements for either of those criteria. All students start with Mathematical Foundations of Machine Learning and progress to courses like NLP, Statistical Machine Learning, and Artificial Intelligence.

  • Top Pick For: Professionals Working Toward ML Engineering; ML-Focused Courses
  • Estimated Tuition: $43,140
  • Typical Length: 1.5–2 years
  • Accreditation: MSCHE
  • AI/ML Specific Credits: 21
  • Total Credits: 30

Why Study ML at Stevens?

Stevens’ M.S. program gets high marks for being one of the few programs on our list with a curriculum that’s sharply focused on machine learning. While other programs go deeper into computer science or data science topics, Stevens’ courses explicitly center on ML theory and applications. For instance, Machine Learning: Fundamentals and Applications will give you dedicated practice in using supervised learning, unsupervised learning, and graphical models.

The program’s electives come from other departments, like Business Analytics and Mathematics, which offer some of the breadth you’d find in other programs like Columbia, but there aren’t a lot of research or industry connections. Despite that, a degree from Stevens still commands attention in the job market. Graduates from Stevens’ School of Engineering and Science, which is the same school that houses the M.S. in Machine Learning, report an average salary of $97,400 within six months of graduation.

LEARN MORE >
6

Purdue University

WEST LAFAYETTE, IN

Overview

M.S. in Artificial Intelligence – AI & Machine Learning major

Purdue University offers an asynchronous M.S. in Artificial Intelligence degree with an AI and Machine Learning track. It’s centered on the creation of AI/ML projects, but it also puts a clear focus on the impact of AI and ethical concerns across sectors. You’ll need a STEM background that includes programming, linear algebra, and probability to be admitted to the program, but once you’re in, the technical requirements are quite low.

  • Top Pick For: ML + Interdisciplinary Studies; Variety of Electives
  • Estimated Tuition: $28,500
  • Typical Length: 1.5–2 years
  • Accreditation: HLC
  • AI/ML Specific Credits: 18
  • Total Credits: 30

Why Study ML at Purdue?

Purdue’s ML program is the highest-ranking program on our list with an interdisciplinary approach. Unlike Stevens’ laser focus on technical ML courses, Purdue provides a basic technical foundation while also expanding on the broader social, political, and economic impacts of AI. Plus, there’s an option to add a concentration in AI Technology Policy and Governance, a rare track that doesn’t appear anywhere else on our list.

You’ll take an AI fundamentals course but, beyond that, the only technical stipulations of the program are that you take at least one AI/ML focused course and one data mining course. This combination makes the program a strong fit if you’re a technically-minded professional who’s moving from deploying ML to shaping how it gets governed and managed.

LEARN MORE >
7

George Washington University

WASHINGTON, D.C.

Overview

Master of Engineering in Artificial Intelligence & Machine Learning

George Washington University takes a decidedly application-focused approach to its Artificial Intelligence and Machine Learning master’s program. You’ll take dedicated courses that cover how to build, utilize, and evaluate AI/ML models in the real world. Because it’s so technical, you’re most likely to succeed if you have a B.S. in engineering or computer science.

  • Top Pick For: Live Online Sessions; Fast Paced; Fixed Course Sequence
  • Estimated Tuition: $37,500
  • Typical Length: 2 years
  • Accreditation: MSCHE
  • AI/ML Specific Credits: 30
  • Total Credits: 30

Why Study ML at GW?

Every student in GW’s M. Eng. program for AI/ML takes the same 10 courses that directly cover a wide variety of ML topics, like computer vision, robotics, deep learning, and Python programming.

This means you’ll be trading flexibility for structure, but GW’s “live online” format gives it a slight edge over Boston University. Classes meet live one evening per week, which gives you direct access to professors. This kind of structured format is also more familiar if you’re the kind of student who typically attends in-person.

Plus, the university’s ties to the federal government ecosystem make the program a strong fit if you want to pursue ML roles with defense, intelligence, and other major agencies. For instance, several faculty members at GW are involved in AI/ML research with the DoD through the Systems Engineering Research Center. The school is also co-leading a program called Trustworthy AI in Law & Society, a program sponsored by the National Science Foundation (NSF) and the National Institute of Standards and Technology (NIST).

LEARN MORE >
8

Boston University

BOSTON, MA

Overview

M.S. in Computer Science & Artificial Intelligence (Online)

Boston University’s M.S. in Computer Science & Artificial Intelligence skips electives and exams in favor of project-based learning. The curriculum combines advanced computer science courses with applied AI projects, many of which you’ll complete with your specific cohort.

  • Top Pick For: Live Online Sessions; Fixed Course Sequence; Fast Paced
  • Estimated Tuition: $25,000
  • Typical Length: 2 years
  • Accreditation: NECHE
  • AI/ML Specific Credits: 27
  • Total Credits: 30

Why Study ML at Boston University?

Boston University’s ML master’s program provides a no-electives, structured path that’s very similar to GW’s program. The difference is that BU takes a very unique approach in requiring 10 project-based modules with no exams. We found this to be a bit less academically rigorous, making the school slip just one spot. Still, this portfolio-heavy approach is great if you’re most interested in gaining a hands-on understanding of how ML models work and how computer infrastructure supports that operation.

However, be mindful that the program uses a highly interactive cohort model of online education. There’s a combination of live sessions and structured asynchronous modules. That, paired with the lack of electives, makes it best suited for students who really crave a structured environment.

LEARN MORE >
9

Old Dominion University

NORFOLK, VA

Overview

M.S. in Data Science & Analytics – Artificial Intelligence & Machine Learning concentration

The master’s degree in Data Science and Analytics from Old Dominion provides an accelerated, data-first approach to AI and ML for students who have bachelor’s degrees in areas like mathematics, engineering, or computer science. The program also provides interdisciplinary options, drawing from the business school and the arts and sciences.

  • Top Pick For: ML + Interdisciplinary Studies; Data-Focused Courses; Fast Paced
  • Estimated Tuition: $19,860
  • Typical Length: 18 months
  • Accreditation: SACSCOC
  • AI/ML Specific Credits: 24
  • Total Credits: 30

Why Study ML at ODU?

ODU’s program requires a solid five foundational data science courses, like Probability Models for Data Science (DASC 603) and Advanced Statistical Concepts in Data Science (DASC 605). Its specialty electives get high marks too. You can study in areas like computer vision, health analytics, cybersecurity, and information retrieval. While ODU is a very strong pick for learning the data pipeline as it relates to ML, it doesn’t have the elite academic status of our fourth-ranked school, Rice.

ODU does have a real advantage on tuition, though. It’s about $16,000 cheaper than the average tuition on this list. That’s especially valuable if you’re looking at research opportunities on a budget. You can take advantage of ODU’s R1 institutional status and its research partnerships with the Naval Research Laboratory and Jefferson Lab. ODU was also recently awarded two AI research projects for NASA worth a total of $2.4M.

LEARN MORE >
10

University of Illinois Chicago

CHICAGO, IL

Overview

Master of Engineering – AI & Machine Learning

The University of Illinois Chicago’s M. Eng. degree is built for students who want to learn how to blend the business side of AI/ML with technical knowledge. In addition to classes like Intro to Machine Learning and Intro to Deep Neural Networks, you’ll also take courses that cover interdisciplinary business strategies and the legal implications of AI/ML.

  • Top Pick For: ML for Business Applications; Fast Paced; Fixed Course Sequence
  • Estimated Tuition: $32,256
  • Typical Length: 12 months
  • Accreditation: HLC
  • AI/ML Specific Credits: 24
  • Total Credits: 36

Why Study ML at UIC?

The M. Eng. from UIC is a broad, structured program that we found to be one of the top picks for ML-in-business studies. Like Purdue, it offers dedicated classes that cover some of the most important topics in the business applications of ML. However, UIC doesn’t offer electives. That means the technical side is a bit weak, but you’ll still take courses in things like computer vision and NLP. It’s also about $4,000 more expensive than Purdue’s program.

A standout addition in UIC’s program is the Engineering Management course that takes the place of a would-be thesis or capstone project. You’ll study the theories, methods, and challenges of project management, which can help you when you’re deploying ML projects and proving ROI to your company’s leaders.

LEARN MORE >
11

Boston University – Metropolitan College

BOSTON, MA

Overview

M.S. in Applied Data Analytics – AI & Machine Learning Concentration

Boston University’s Metropolitan College has designed its M.S. in Applied Data Analytics program, with a concentration in AI and ML, specifically for professionals who are designing and deploying ML models for strategic business purposes across industries. For research-minded students who want to spend more time in the program, there’s also an optional eight-credit thesis project.

  • Top Pick For: Non-Tech Undergrad Majors; Thesis Project
  • Estimated Tuition: $32,675
  • Typical Length: 8–20 months
  • Accreditation: NECHE
  • AI/ML Specific Credits: 32–40
  • Total Credits: 32–40

Why Study ML at BU MET?

BU’s master’s program for Applied Data Analytics is not an exclusively computer-science-focused degree. That makes it a strong fit that’s much more accessible for students who have non-technical undergraduate degrees in areas like economics or business. If you have that type of degree, you can get up to speed in this program with “preparatory labs,” covering calculus, probability, and database fundamentals, to make sure you have a solid foundation before beginning the program.

You can expect less technical curriculum than higher-ranking programs like Stevens or UNM, but there’s flexibility in this program: you pick electives, you can complete a thesis or not, and you can be done in less than two years.

LEARN MORE >
12

Drexel University

PHILADELPHIA, PA

Overview

M.S. in Artificial Intelligence & Machine Learning

Drexel’s M.S. in Artificial Intelligence & Machine Learning degree provides academic depth with an even mix of data science, ML theory, and ML applications. It comes at a steep cost, though, so it’s worth taking a thorough look at financial aid options before putting it on your shortlist.

Because Drexel currently operates on quarter terms, the program is listed as 45 credits. That’s equivalent to 30 credits in a semester-based program. However, Drexel will be switching to a semester schedule in the fall of 2027.

  • Top Pick For: Customized Degree; Non-Tech Undergrad Majors
  • Estimated Tuition: $66,645
  • Typical Length: 2 years
  • Accreditation: MSCHE
  • AI/ML Specific Credits: 27 (quarter credits)
  • Total Credits: 45 (quarter credits)

Why Study ML at Drexel?

We gave Drexel’s AI/ML master’s program a high score for its curriculum, but the tuition cost really holds back this program and knocks it out of our top 10. At nearly $67,000, it’s the second most expensive program on our list, right behind Columbia at $85,000, but it doesn’t offer nearly the prestige and breadth as Columbia. Still, the name recognition and earning potential are there. According to data from Georgetown University’s Center on Education and the Workforce, Drexel ranks in the top 4% of U.S. universities for the highest lifetime earnings of students.

Drexel’s program offers two solid academic paths. There’s a computational concentration and an applied concentration, each with its own curriculum. You’ll get to do a capstone, too. This hands-on experience puts it just ahead of a program like WGU, if you can afford the tuition. If you need a more affordable option, check out Georgia Tech for the computational side or Northeastern University for the applied side.

LEARN MORE >
13

Western Governors University

MILLCREEK, UT

Overview

M.S. in Computer Science – AI & Machine Learning specialization

For motivated learners who are confident in their technical foundations, Western Governors University’s M.S. in Computer Science degree has the potential to be a very affordable option. You can specialize in AI & Machine Learning and progress through the program completely at your own pace. Once you’re ready, you can take each course’s final assessment and, if you pass, you’ve fulfilled the requirement.

  • Top Pick For: Affordability; Fast Paced; Independent Learners
  • Estimated Tuition: $13,155
  • Typical Length: 18 months
  • Accreditation: NWCCU, ABET
  • AI/ML Specific Credits: 7 courses (competency-based)
  • Total Credits: 10 courses (competency-based)

Why Study ML at WGU?

If you’re a self-directed learner, you’ll appreciate the independence you’ll have as you work through WGU’s program. Tuition is a set rate that’s paid per six-month term. There’s no limit to how many units you can take each term. So, the quicker you move through the course material, the less you’ll pay for your degree. However, if you’re not solid on your technical knowledge or you have trouble staying on schedule, this degree program could end up costing you more in the end.

WGU is another program, like BU, that doesn’t do traditional exams. Instead, each course requires a “performance assessment” that may take the form of a report, presentation, or project. This is a hands-on way of proving competency that can also provide a boost to your portfolio.

You’ll also earn the AWS Certified Machine Learning Engineer – Associate certificate as part of the master’s degree at WGU. That certificate, along with your increased expertise in AI/ML, is likely to result in a higher salary. WGU data shows that graduates report an average salary increase of $13,785 after finishing a School of Technology graduate program.

LEARN MORE >
14

Tarleton State University

STEPHENVILLE, TX

Overview

M.S. in Artificial Intelligence & Machine Learning

Tarleton State University’s online M.S. in Artificial Intelligence & Machine Learning degree is one of the few on our list that offers a dedicated thesis track alongside its more traditional professional track. This program is typically reserved for technical professionals who have a bachelor’s degree in computer science.

  • Top Pick For: Engineering Undergrad Majors; Thesis Project
  • Estimated Tuition: $25,956 (professional track)
  • Typical Length: 2 years
  • Accreditation: SACSCOC
  • AI/ML Specific Credits: 18–21
  • Total Credits: 36 (professional track); 33 (thesis track)

Why Study ML at Tarleton?

Tarleton’s online M.S. program offers two customized tracks, but it’s a very new program. Launched in spring 2025, it has a limited course catalog of only eight electives and a track record that can’t stand up to programs like Georgia Tech.

The program’s advantage is that both its professional and thesis tracks include many instances of project-based learning with the access and attention you need to succeed. The student-to-faculty ratio in Tarleton’s Department of Computer Science and Electrical Engineering graduate programs is very low, 10:1, so you’ll also enjoy direct access to professors that you can’t get at bigger schools. This will give you a guided, hands-on introduction to modern ML and tools, including robotics, reinforcement learning, deep neural networks, and parallel computing.

LEARN MORE >
15

Columbia University

NEW YORK, NY

Overview

M.S. in Computer Science – Machine Learning track (Columbia Video Network)

The M.S. in Computer Science degree from Columbia University has an Ivy League price tag and a course load to match. There isn’t a thesis or capstone requirement for Columbia’s program, but the rigorous curriculum goes into advanced ML topics like Bayesian models and sparse signal modeling.

  • Top Pick For: Customizable Degree; Specialized Electives
  • Estimated Tuition: $84,660
  • Typical Length: 2–4 years
  • Accreditation: MSCHE
  • AI/ML Specific Credits: 24
  • Total Credits: 30

Why Study ML at Columbia?

Earning a degree through Columbia’s Ivy League engineering school will give you extensive experience in the systems, theory, and applications of ML, but that comes at a serious cost. This program is the most expensive one on our list. It’s more than $49,000 over the average tuition of our top 20. You won’t get the chance to do a thesis or capstone at Columbia, either. This means you’ll likely have fewer industry contacts and instances of hands-on experience.

If you’re ready to commit to the tuition price, you’ll get to pick from an unusually broad course selection (50+ electives) that’s unlike any other master’s degree program on our list. Many of the courses are labeled as “advanced,” so if you’re already comfortable with the foundational concepts, you can go right into the niche topics of ML. For instance, you can choose from Advanced Database Systems, Advanced Spoken Language Processing, and Advanced Robotic Manipulation.

Still, the programs at both Stevens and UNM offer much of this technical depth, plus access to faculty and industry experts, at a fraction of the cost.

LEARN MORE >
16

Northeastern University

BOSTON, MA

Overview

Master of Professional Studies in Applied AI

Northeastern University’s M.P.S. in Applied AI is focused on giving working professionals the real-world skills they need to build and implement AI/ML projects. Instead of focusing on a computer science foundation, the program builds knowledge in specialty areas of ML.

  • Top Pick For: Applied ML; Customized Degree; Specialized Electives
  • Estimated Tuition: $30,500
  • Typical Length: 12–20 months
  • Accreditation: NECHE
  • AI/ML Specific Credits: 18–30
  • Total Credits: 34

Why Study ML at Northeastern?

Northeastern’s M.P.S. in Applied AI offers three specific AI/ML concentrations: Machine Learning for Cybersecurity, AI for 3D Imaging, and Conversational AI and Chatbots. Each concentration offers specific elective classes that are hard to find elsewhere. Depending on your interests, you could take Machine Learning for Cyberdetection (AAI 6690), Chatbot Architecture (AAI 6660), or Deep Learning for 3D Point Cloud Analysis (AAI 6730). By taking these specialized courses, you gain expertise that has the potential to be immediately applied to your industry.

Judging it against the other programs, Northeastern is a little below average in terms of cost, rigor, and timeline. Georgia Tech is much cheaper and UIC is faster. If you’re considering Northeastern for cybersecurity, be sure to compare it to ODU, which is about $10,000 cheaper and also offers specialty electives.

LEARN MORE >
17

Southern Methodist University

DALLAS, TX

Overview

M.S. in Data Science – Machine Learning & Artificial Intelligence specialization

The online M.S. in Data Science degree from Southern Methodist University is the only one on our list with in-person requirements, which come at the beginning and end of the program. For the rest of your studies, you’ll get a combination of recorded lectures and independent coursework alongside live, online classes.

  • Top Pick For: Live Online Sessions; Data-Focused Courses; Industry Experience
  • Estimated Tuition: $41,205
  • Typical Length: 20–28 months
  • Accreditation: SACSCOC
  • AI/ML Specific Credits: 21
  • Total Credits: 33.5

Why Study ML at SMU?

SMU’s master’s in data science program puts a heavy emphasis on networking between students, professors, and industry leaders. But it isn’t truly a 100% online program because it requires two on-site immersions on campus in Texas. This structure also provides weekly live sessions with small, seminar-style groups, which is something asynchronous programs like WGU and Purdue can’t offer. If you live relatively close to campus, this is a great option for building connections that could land you an ML role.

Keep in mind that SMU’s curriculum puts a very heavy focus on data science. If you’re pursuing research, you submit your papers to the SMU Data Science Review, a journal specifically for the work of master’s students at the school. However, this is a tradeoff. The program definitely has a thinner focus on ML. At SMU, you’ll take just two dedicated electives in the AI/ML area, while programs like ODU and BU MET provide more room to specialize in ML.

LEARN MORE >
18

Georgia Southern University

STATESBORO, GA

Overview

M.S. in Computer Science – Machine Learning concentration

Georgia Southern University’s M.S. in Computer Science degree leans heavily into ML-focused topics with three distinct tracks (thesis, non-thesis, and research project) so you can shape your degree around your goals. With a minimum undergrad GPA of 2.5, it’s a solid option if you want a program with accessible admissions standards and a less rigorous technical curriculum.

  • Top Pick For: Technical Undergrad Majors; Customized Degree; Thesis Project
  • Estimated Tuition: $34,800
  • Typical Length: 20 months
  • Accreditation: SACSCOC
  • AI/ML Specific Credits: 15
  • Total Credits: 30

Why Study ML at Georgia Southern?

For some students, Georgia Southern’s program will provide just the right amount of structure versus freedom for an add-on to a CS degree. With only five choices for courses in the ML concentration track, it’s approachable but doesn’t have the level of technical depth needed to rank higher on our list. You’ll take three ML concentration classes, but the curriculum is quite basic and doesn’t offer any opportunities to study advanced tools or theories.

However, Georgia Southern’s program is the only one on our list that pairs a master’s in computer science with a thesis project. If you want the research credentials to back up your CS-specific degree, it’s a strong pick.

LEARN MORE >
19

Milwaukee School of Engineering

MILWAUKEE, WI

Overview

M.S. in Machine Learning

The M.S. in Machine Learning from the Milwaukee School of Engineering is expressly designed to teach engineers how to build and deploy ML products to solve industrial problems. You are expected to have programming experience and knowledge in calculus or linear algebra before beginning the program.

  • Top Pick For: Engineering Undergrad Majors; Applied ML; Fixed Course Sequence
  • Estimated Tuition: $54,976
  • Typical Length: 1–4 years
  • Accreditation: HLC
  • AI/ML Specific Credits: 20
  • Total Credits: 32

Why Study ML at MSOE?

MSOE offers four stackable certificates that are directly applicable to industry: Tiny Machine Learning, Generative AI Production Systems, Applied Machine Learning, and Machine Learning Engineering. In each certificate, you’ll get to use the school’s supercomputer, Rosie, for projects and coursework.

The program has an admittedly narrow focus, and it’s very expensive too, about 8x the price of Georgia Tech. However, if you’re an engineer wanting to break into ML, that applied focus and portfolio projects are exactly what you’ll need to step into a specialized role.

The program is also accessible for professionals who want to ramp up to a full ML program. Each certificate can transfer directly into the master’s program. You might want to take the Applied Machine Learning certificate first, before committing to the entire master’s program.

LEARN MORE >
20

Colorado State University Global

AURORA, CO

Overview

M.S. in Artificial Intelligence & Machine Learning

Colorado State University Global’s fully online M.S. in Artificial Intelligence and Machine Learning program is fast, approachable, and offers fairly affordable tuition. It does not require any prior experience in advanced technical studies, but you’ll also see that lack of technical emphasis throughout the curriculum.

  • Top Pick For: Fast Paced; Fixed Course Sequence; Non-Tech Undergrad Majors
  • Estimated Tuition: $20,250
  • Typical Length: 12–18 months
  • Accreditation: HLC
  • AI/ML Specific Credits: 12
  • Total Credits: 30

Why Study ML at CSU Global?

CSU offers lots of flexibility via asynchronous learning and monthly start dates, but it falls short in academic offerings and hands-on practice. Each of its eight required technical courses provides basic foundational knowledge, but none go deep into ML-specific theories or applications. The remaining two required courses are focused on management and leadership.

Still, CSU Global is one of the cheapest ML master’s programs on our list, right behind UNM and ODU. It’s also one of the fastest programs, making it a good option if you want to wrap up your studies in about a year.

The combination of speed and cost savings, along with foundational academics, makes it a solid pick for tech-minded business professionals. But if you want academic rigor and a program with a notable reputation, go with Georgia Tech.

LEARN MORE >

Methodology: How We Reviewed and Ranked the Online Master’s in Machine Learning Degrees

For the Programs.com list of the top 20 online master’s in ML degree programs, we only evaluated programs with online degree pathways and coursework relevant to ML, AI, computer science, computer engineering, and data science. We also limited our analysis to programs that are institutionally accredited.

Our weighted algorithm accounted for the following criteria:

Each program received a score of 0-100 for each ranking factor. We multiplied the score by that factor’s assigned weight and added the results to calculate the program’s overall ranking score.

We made a few adjustments based on what students consider most important when evaluating online master’s in ML programs.

Who Should Consider an Online ML Master’s Degree?

An online ML master’s degree is typically designed for working professionals who want to advance into AI/ML-focused roles or simply deepen their expertise in their field.

People who are considering this type of degree typically fit into one of these categories:

Current IT Professionals: Online master’s in ML programs are an ideal fit for early and mid-career IT workers who want to switch to an AI/ML-focused role. If you have a bachelor’s in computer science or computer engineering, you’ll be well equipped to start a graduate program in ML.

Georgia Tech’s OMSCS degree is one of the best picks for IT professionals. It’s technically broad, providing 75+ elective options so you can specialize in the area of ML that you’re targeting for your new role. Or, for another challenging degree program, look at Stevens Institute of Technology. Its master’s program has a heavy ML-focused course load that’s ideal if you’re working toward an ML engineering role.

Professionals with a STEM Background: Even if you’re coming from a background in mathematics, statistics, or data science, there are online master’s in ML programs that will work for you.

Boston University’s Metropolitan College and WGU offer remedial courses in topics like Python or algorithms to get you ready for master’s studies. Both of these programs are ideal for upskilling even if you’re not totally confident in programming or advanced technical concepts.

Aspiring ML Specialists: If you’re interested in a niche area of ML, an online master’s degree can provide the advanced learning you need. Compare programs to find the electives and concentrations you’re most interested in pursuing, whether that’s computer vision, bioinformatics, or tinyML.

For example, Columbia’s online master’s in ML program is ideal for people who want to specialize in signal processing. You can follow a path of at least five electives in this niche area. You should also take a look at Northeastern’s ML program. Its electives are very specialized, offering technical depth you won’t find anywhere else. For instance, Northeastern offers electives in applying ML to 3D imaging, an option that’s ideal if you want to pursue roles in the biomedical or manufacturing sectors.

Business Professionals Working with ML: Product managers, data analytics leaders, content strategists, and other non-technical professionals are increasingly managing AI/ML initiatives. An online master’s in ML can provide a deeper understanding of how these initiatives are built, deployed, and governed.

Your two best options on our list are the University of Illinois Chicago and Boston University – Metropolitan College. Both of these master’s programs are focused on the business implications of machine learning. They can also be completed in about a year, which is an important advantage if you’re working in a high-profile business role in addition to your master’s studies.

Research-Focused Students: Although on-campus learning is a more traditional path for research-focused students in ML, certain online master’s programs do provide the opportunity to work on research projects with faculty, complete a thesis, or pursue a research-oriented capstone.

Many of the schools on our list are R1 institutions: Drexel, George Washington, and Columbia, just to name a few. However, you’ll want to look for a program with dedicated opportunities in your area of interest. You can browse through ODU’s ML master’s program and the dozens of research opportunities through its partnership with the computer science department. Or, take a look at Georgia Southern University, which offers options for both a thesis and an applied ML research project.

Choosing the Right Machine Learning Master’s Degree Program

With all of the hype surrounding machine learning, it’s tempting to pick the online master’s program that sounds the most exciting or innovative. In reality, you should base your choice on the school’s curriculum and your personal criteria like your background, career goals, budget, and learning preferences.

Here are a few more distinctions to look for when picking the right online ML master’s program for you.

Data Science vs. Computer Science

Just by browsing through our rankings, you can see that ML master’s programs go by lots of different names. Programs that are closely associated with computer science departments are going to be the most technically advanced degree paths, like the academically focused programs from Columbia and Georgia Tech. Oftentimes, these programs only admit people with bachelor’s degrees in computer science.

If you have a non-technical background, a master’s in data science (like from SMU) or professional studies (like from Northeastern) might be the best choice.

Concentration or Major?

Some master’s programs offer named degrees that specify “machine learning” or “artificial intelligence.” Tarleton State, University of Washington-Seattle, and Drexel are three of the 11 on our list that offer this. The others offer concentrations or specialized tracks.

Programs with concentrations in ML typically allow you to pursue more interdisciplinary studies while earning your master’s degree. You’ll want to narrow your focus to these types of programs if you’re interested in taking a few courses in business management, leadership, AI ethics, social sciences, and healthcare. Columbia, for example, offers a course in Modeling Social Data, which looks at data collection, engineering, and research from a large-scale social perspective.

On the other hand, if you want more opportunities in the niche areas of ML and more advanced electives, you should pursue a named degree. For instance, in the named program from the University of Washington-Seattle, you can choose from advanced certificates like Data-Driven Dynamic Systems & Control for Engineering. Here are the specific courses in that certificate:

Fixed or Flexible?

If you prefer a degree path that’s already set for you, choose an ML master’s program with a fixed curriculum. These programs offer a straightforward course progression that works best for students who mostly want to cover ML with broad strokes. However, if you’re interested in specific areas of ML or simply prefer to chart your own path, look for a program with plenty of electives. On our list, Georgia Tech and Columbia offer the most options for electives, while CSU Global is a good pick for a fixed, basic ML master’s degree.

Hands-On Experience

Building your portfolio is an important part of earning your master’s degree in ML. Class projects are helpful for developing individual skills, but hands-on experience with real-world data is even more impressive to mention on your resume and in job interviews. When evaluating programs, look for options like capstone projects, client-sponsored projects, and faculty that specialize in the type of experience you’d like to gain.

Connections to Industry

Choose a program with connections to the industry you’d like to work in. For instance, if you’re interested in government or DoD work, George Washington University’s online master’s in ML might be a good fit. Or, if you’re interested in applying ML in the finance sector, Georgia Tech offers a three-part electives course on Machine Learning for Trading.

Online Master’s Degree in Machine Learning Coursework, Curriculum, and Program Structure

Online ML master’s degrees typically offer a combination of lectures, independent coursework, and applied projects. Here’s what you can expect.

Program Structure

Most online master’s programs require between 30 and 36 credits to complete. You can take anywhere from one year to five years to earn the degree.

If you are a non-technical professional entering a technical program, you may be required to complete a few foundational courses before you begin the master’s program. This requirement varies between schools. Some are very strict (like Stevens), and others evaluate each student on a case-by-case basis (like BU MET).

The majority of these online programs are asynchronous, meaning that all of the materials are provided and learning is totally independent. However, a few offer some “live” components, like weekly class lectures, discussion groups, or even on-campus events.

Common Courses in an Online ML Master’s Program

There are three main categories of courses in online master’s of ML programs:

SchoolCore ML Credits
Georgia Institute of Technology15 credits
University of New Mexico13–16 credits
University of Washington–Seattle28–29 credits
Rice University24 credits
Stevens Institute of Technology21 credits
Purdue University18 credits
George Washington University30 credits
Boston University27 credits
Old Dominion University24 credits
University of Illinois Chicago24 credits
Boston University MET32–40 credits
Drexel University27 credits
Western Governors University7 courses
Tarleton State University18–21 credits
Columbia University24 credits
Northeastern University18–30 credits
Southern Methodist University21 credits
Georgia Southern University15 credits
Milwaukee School of Engineering20 credits
Colorado State University Global12 credits

Thesis and Capstone Project

Depending on the program and path you choose, you might complete a thesis or capstone project.

Theses are relatively rare in online master’s in ML programs. This is because they’re research-focused, which is a path typically pursued by on-campus students who plan to continue on to doctoral programs. However, in a program like Tarleton State with a dedicated thesis requirement, you’ll likely work with a faculty member to identify a research question and work through the research and analysis process over the course of one or two semesters.

Capstone projects are much more common in online ML master’s degree programs. Rather than focusing on academic research, you’ll apply your ML expertise to a real-world challenge. In many programs, you get to connect with external organizations or businesses that have partnerships with the university. Capstone projects typically involve working with a team, but they can be completed independently in some cases.

Online Machine Learning Graduate Degree FAQs

What Roles Do Machine Learning Master’s Degrees Prepare You For?

Getting a master’s degree in machine learning can set you up for several technical roles. Oftentimes, these roles explicitly require an advanced degree in AI or ML. We’ve listed some of the most common roles in the table below. We’ve also included their salary ranges, but keep in mind that industry sources vary. For instance, Levels.fyi and Glassdoor include stock options and bonuses in their figures, while ZipRecruiter does not.

Job TitleMedian Annual Compensation
Machine Learning Engineer$139,000 (ZipRecruiter) to $280,000 (Levels.fyi)
AI Engineer$102,000 (ZipRecruiter) to $154,000 (Levels.fyi)
MLOps Specialist$129,000 (ZipRecruiter) to $150,000 (Levels.fyi)
AI/ML Research Scientist$130,000 (ZipRecruiter) to $169,000 (Levels.fyi)
Computer Vision Specialist$122,000 (ZipRecruiter) to $169,000 (Glassdoor)
NLP Engineer$107,000 (ZipRecruiter) to $166,000 (Glassdoor)
Robotics Engineer$106,000 (ZipRecruiter) to $146,000 (Glassdoor)

Will Employers Care That My Machine Learning Degree Is Online?

In most cases, your formal degree name will not mention that you earned it through an online program. You earn the same exact degree as on-campus learners.

However, degrees from some programs naturally reveal their online status. This includes WGU and CSU Global, neither of which has a physical campus.

In today’s digital world, most employers will care far more about the program’s curriculum, accreditation, and reputation than the online format. As long as you can show your technical abilities and a relevant portfolio, you likely won’t run into any problems.

What Other Ways Can I Get an ML Role Besides a Graduate Degree?

A master’s degree isn’t the only path to getting a job in machine learning.

One way to work toward an ML role is to take select online courses or complete bootcamp-style classes. The most important individual skills to learn are Python, linear algebra, algorithms, and the basics of neural networks and deep learning.

If your job is already in a technical field, you can look for ways to gradually incorporate machine learning into your current role. As a start, you could ask your employer if you can gain more experience working with data, like forecasting or analytics. You may be able to learn SQL or learn data pipeline workflows without changing roles at all.

You can also pursue formal certificates related to ML. These are much shorter than full graduate programs, typically requiring just a few courses to complete. If you decide to pursue a master’s degree in the future, credits from certificates are likely to transfer.

How Much Does an Online Machine Learning Master’s Program Cost?

The tuition cost of the programs on our top-20 list ranges from $6,750 (Georgia Tech) to $84,660 (Columbia University). The average cost is about $35,500. As you can see, an online degree is not automatically cheaper than on-campus options.

If you have a clear path to an ML-related role, you are the most likely to see the benefits outweigh the costs of a master’s in ML program. This is especially true if you are already in a technical role. You can use this additional expertise in ML to pivot to a more specialized role and likely demand a higher salary.

For some people, higher tuition costs could be worth it if the program is tied to direct industry experience and connections. Industry-leading faculty, strong alumni networks, and impactful capstone projects can deliver tangible returns like referrals and job offers.

Without a technical background, you are less likely to see the value in a high-cost master’s program. You may need several preparatory classes and struggle to learn ML theories and tools from scratch. Lower-cost certificates are likely to be the best path forward if you’re in this group.