Best Master's in AI Degree Programs for 2026

Compare AI Programs at Stanford

Instead of a standalone graduate degree in artificial intelligence, Stanford offers rigorous on-campus and online master’s programs in computer science that can be customized with AI coursework.

• The best choice for research-focused AI students is the full-time CS master’s degree from Stanford Engineering. The MS CS is available in multiple specializations—we’ve highlighted just a few of the options. This terminal, on-campus degree takes ~1.5 years to complete and features the standard assortment of foundation, breadth, depth, and elective credits in AI. See the degree requirements for more info. You’ll be able to apply for Course Assistantship (CA) and Research Assistantship (RA) positions and pursue a distinction in research.
• In contrast, the 100% Online MS CS – Artificial Intelligence is available in a full-time format (1-2 years) or a part-time format (3-5 years) through the Honors Co-op Program (HCP). Only the AI, Information Management and Analytics, and Systems specializations are available online and you must reside in the United States in order to apply.

We were also intrigued to discover that Stanford’s Center for the Study of Language and Information has developed a research-focused Master of Science (MS) in Symbolic Systems. It’s a fascinating pick for anyone exploring high-level theoretical questions around language, information, and artificial intelligence. See the degree requirements for examples of course titles.

Note: Virtual learners can start by enrolling in Stanford Engineering’s Online Artificial Intelligence Graduate Certificate. Credits can be applied toward the MS CS.

What Makes Stanford a Great Artificial Intelligence School?

Located in Silicon Valley, Stanford is one of the world’s leading AI universities, with god-like strengths in advanced artificial intelligence research. It also generates an incredible return on investment (ROI). 4-5 years after graduation, some Stanford computer science graduates are earning in excess of $331k per annum. The internationally renowned Stanford Artificial Intelligence Lab (SAIL) has been in existence since 1963, and it provides students with unique opportunities to tackle real-world challenges. Industry affiliates such as Google, Accenture, and UST Global sponsor AI projects and partner with faculty & students.

Before applying for the MS CS, take a look at the profiles of CS faculty with an especial interest in AI research, including work at the Stanford Translational AI (STAI) Lab. Then visit the interdisciplinary Stanford Institute for Human-Centered AI (HAI). HAI offers a 3-quarter graduate fellowship program to on-campus graduate students who are dedicated to human-centered AI. For news on the university’s latest research developments, visit the Stanford Report’s section on Artificial Intelligence and HAI’s annual AI Index Report.

Compare AI Programs at UC Berkeley

Although UC Berkeley doesn’t offer a dedicated master’s in artificial intelligence, it does have MS and MEng programs that can be tailored to fit. It’s important to understand the distinction between the two degree titles:

• Two-year Master of Science programs at UC Berkeley are typically designed to augment or lead to a PhD. Very few students are admitted to a MS-only program; most successful applicants are enrolled in a MS/PhD pathway. If you are ready for that kind of research path, you can’t do better than the Department of Electrical Engineering & Computer Sciences (EECS). Artificial intelligence students in the MSCS and MS in EECS will have the opportunity to collaborate with faculty in multiple research centers & labs, including the famous Berkeley Artificial Intelligence Research Lab (BAIR).
• The Department of EECS’s professional alternative to the MS is the on-campus Master of Engineering (MEng). Although there is no concentration in AI for this terminal degree, there are opportunities to specialize in data science and robotics and embedded software. Keep in mind that this MEng is a technical qualification. Mechanical engineers with a hands-on interest in robotics should consider the MEng in Control of Robotic and Autonomous Systems from the Department of Mechanical Engineering instead.

If none of these suit, virtual learners with quantitative & programming skills can apply to UC Berkeley’s Online Master of Information and Data Science (MIDS) from the School of Information.

What Makes UC Berkeley a Great Artificial Intelligence School?

UC Berkeley’s strategic location in the Bay Area gives AI graduate students unprecedented access to Silicon Valley opportunities. Along with Stanford, UC Berkeley is also known for having a world-class reputation in artificial intelligence research. In addition to the groundbreaking AI work being done within BAIR, the university sponsors scores of initiatives in human compatible AI, robotics & ML, enhanced reality (e.g. VR and AR)—the list never ends.

UC Berkeley was one of the first law schools in the world to offer an advanced degree with a specific AI-law focus. It has strategic partnerships with many Silicon Valley corporations (be sure to check out the sponsors of the Sky Computing Lab). And, in March 2024, it launched a new AI-focused Center for Healthcare Marketplace Innovation (CHMI), led by the College of Computing, Data Science, and Society and the Haas School of Business. In terms of name recognition, it’s one of the best of the best.

Compare AI Programs at CMU

Carnegie Mellon University (CMU) offers an extensive range of master’s degrees in artificial intelligence & machine learning, including a unique, innovation-focused MS for entrepreneurs.

• Research-minded students with a technical background can apply for the School of Computer Science’s highly regarded on-campus MSML, with the option to proceed to a PhD. This 3- or 4-semester degree includes an internship or research-related practicum in the summer semester.
• Electrical and computer engineering (ECE) professionals will be happy to hear that CMU’s College of Engineering has developed an efficient, three-semester MS in AIE for those who are seeking to design and build AI-orchestrated systems.
• Professionals with a specific interest in intelligent information systems can consider the practice-based MIIS from the Language Technologies Institute. The MIIS features concentrations in Human Language, Machine Learning, and Language Technology Applications.
• Anyone focused on the intersection of AI and startups should investigate the MSAII from the School of Computer Science. In the first year, you’ll have the opportunity to explore future markets, AI law, and AI engineering. In the second year, you’ll collaborate with a team on an industry-sponsored capstone project.

CMU has also begun catering to business & management professionals who need a practical qualification in artificial intelligence systems & applications. The Heinz College of Information Systems and Public Policy now offers a 12-month AIM program that explores high-level ideas around AI strategy, decision modeling, AI financial evaluations, and more.

What Makes CMU a Great Artificial Intelligence School?

Carnegie Mellon University is internationally renowned for its strength in artificial intelligence, especially in the realm of applied AI. See AI at CMU for an overview. The School of Computer Science (SCS) created the world’s first machine learning academic department in 2006 and it’s advancing leaps & bounds in AI research. CMU has scores of projects on the boil with industry & government partners, including DARPA. It runs the CMU-NIST Cooperative Research Center AI Measurement Science & Engineering (AIMSEC). It supports the NSF AI Institute for Societal Decision Making (NSF AI-SDM). And it has a dedicated Center for Machine Learning and Health (CMLH).

CMU’s location in Pittsburgh also means it has a vested interest in advanced manufacturing. If you are eyeing the Master of Science in Robotics (MSR), be sure to visit the Robotics Institute, the Manufacturing Futures Initiative (MFI), and the National Robotics Engineering Center (NREC). The university has close ties to the federally-backed Advanced Robotics for Manufacturing (ARM) Institute, a DoD Manufacturing Innovation Institute, and the Pittsburgh Robotics Network (PRN), an industry-university coalition.

Compare AI Programs at Georgia Tech

Georgia Tech offers its versatile Master of Computer Science (MSCS) in an on-campus and online format.

• The traditional MSCS is a highly selective terminal degree program that comes in three formats: coursework-only, capstone project, and research thesis. It’s very easy to customize a specialization to suit your professional area of interest. For instance, in the Artificial Intelligence track, you only have to take one course in algorithms & design before exploring AI credits and electives in AI methods, interactions, and cognition.
• The Online MSCS is almost exactly the same, but coursework is asynchronous (learn-on-your-own-time) and more limited than the on-campus program. See the curriculum list under each specialization; online courses are highlighted in bold. Unlike many asynchronous degrees, the OMSCS program does a stellar job of encouraging collaboration through local meet-ups, a hybrid conference, project showcases, virtual coffee hours, and more. Browse through the faculty profiles and read the FAQs for a comprehensive sense of the experience.

We’ve also highlighted a number of options for robotics students. The Computational Perception & Robotics concentration in the MSCS explores topics such as autonomous systems, human-robot interaction (HRI), and interactive robot learning. The 4-semester, professional Master of Science in Robotics (MS Robotics) has much more of an engineering feel, with core courses in areas such as mechanics, control, perception, AI, HRI, and natural systems.

What Makes Georgia Tech a Great Artificial Intelligence School?

Georgia Tech is famous for intellectual rigor and the real-world applicability of its AI coursework. Tech AI, the AI Hub at Georgia Tech can provide you with a broad overview, but more detailed information on AI labs & institutes is available through the School of Interactive Computing’s section on Artificial Intelligence & Machine Learning and the School of Computational Science and Engineering’s summary of AI & ML engineering research. In 2024, the NSF awarded $20M to Georgia Tech and its partners to develop the Nexus supercomputer. Nexus will help boost the grunt of the College of Engineering’s AI Makerspace, a digital sandbox for students created in collaboration with NVIDIA.

Interested in forging connections with potential employers? Georgia Tech serves as the lead institution for the NSF AI Institute for Advances in Optimization (AI4OPT), which drives industry-focused R&D initiatives such as the Kinaxis co-innovation partnership on global supply chains. In addition, the university funds the Georgia Tech Manufacturing Institute (GTMI), which oversees the AI Manufacturing Pilot Facility (AIMPF) and works closely with the Partnership for Innovation (PIN) on AI manufacturing & logistics challenges.

Compare AI Programs at UIUC

The Siebel School of Computing and Data Science at UIUC has developed two degree pathways for artificial intelligence graduate students.

• The first pathway is a rigorous, research-oriented MS in CS with a mandatory thesis. This full-time master’s program will also give you an opportunity to apply for research and teaching assistantships. It must be completed within five consecutive semesters and credits can be counted towards the PhD in Computer Science.
• The second option is the affordable, coursework-only Master of Computer Science (MCS) – Artificial Intelligence, which is available in Chicago, Urbana-Champaign, and online. Full-time or part-time study is available. Designed for professionals, this MCS is open to applicants with an undergraduate degree in computer science or those with commensurate experience & coursework. Students who select the Artificial Intelligence specialization can choose three courses in areas like AI, machine learning, NLP, and deep learning for healthcare.

Focusing on robotics? Within UIUC’s Center for Autonomy lies the professional MEng in Autonomy & Robotics. We’ve highlighted this degree because of the coursework in algorithm design and ML, the option to select electives in AI and perception, and the inclusion of a capstone project or professional practicum. It’s a strong qualification for those who are working toward technical & managerial roles in the autonomy and robotics industries.

What Makes UIUC a Great Artificial Intelligence School?

UIUC is the Midwest’s most prestigious academic player in AI, frequently ranking in the top 10 universities in the USA for artificial intelligence research. The Siebel School has a useful summary of its AI strengths and faculty projects, but we also recommend a visit to the Grainger College of Engineering’s section on AI Centers & Initiatives. Here you’ll find info about the IBM–Illinois Discovery Accelerator Institute (IIDAI), which is dedicated to advancing hybrid cloud, AI, quantum, and accelerated materials discovery. Then head over to the National Center for Supercomputing Applications (NCSA) to learn more about the Center for Artificial Intelligence Innovation (CAII).

Trying to persuade your employer to help sponsor your degree? UIUC is an excellent choice for working professionals and those on a budget. In 2026, the Online MCS with asynchronous coursework was under $30k, even for non-residents and international students. That’s half the cost of some of the other online master’s programs in our Best rankings. We’ve already mentioned the Center for Autonomy, but robotics students should also investigate the research labs within the Illinois Robotics Group. UIUC has an abiding interest in agtech, and a couple of the associated robotics centers are devoted to agriculture applications.

Compare AI Programs at UW

Technically-focused graduate degrees in AI at the University of Washington are offered through the Allen School and UW Engineering. These Professional Master’s Programs (PMPs) are designed for working professionals who would like to maintain their job while they study.

• Those with a computing background should investigate the part-time, on-campus MSCS with evening classes in Seattle. Successful applicants for this program have an average of 5 years of professional experience. Core coursework often encompasses ML, HCI, deep learning & AI applications and graduates tend to be employed by industry leaders such as Amazon, Microsoft, Google, and Boeing.
• Concentrating on the physical side of engineering? An online PMP pathway is also available for mechanical & chemical engineers who would like to apply AI and ML methods to work in areas such as manufacturing, robotics, and chemical processes. The Online MS in AI and ML for Engineering is built on a stackable model—you’ll earn two industry-focused graduate certificates before embarking on your capstone project. And faculty are nothing less than brilliant.

However, if you need a basic primer on AI, your best bet will be the MSIM from the Information School. It’s open to applicants with a bachelor’s degree in any discipline. We’ve also featured specialist degrees in our list of offerings in case you’ve decided to focus on robotics or computational linguistics.

What Makes UW a Great Artificial Intelligence School?

UW is a major name in AI education on the West Coast and a well-known feeder for big tech firms in Seattle. Within the Paul G. Allen School of Computer Science & Engineering, you’ll discover a wide array of AI research groups & labs. Across UW Engineering, the landscape expands to include applied AI centers & institutes in areas such as dynamic systems, robotics, and neurotechnology. Check out the NSF-funded AI Institute in Dynamic Systems, as well as the eScience Institute and its Data Science & AI Accelerator. Better yet, UW has deep & longstanding partnerships with Amazon and NVIDIA and works closely with the Allen Institute for AI (AI2) and the Center for AI @PNNL.

Anyone with a special interest in AI theory can connect with the Institute for Foundations of Data Science (IFDS), an NSF-funded, multi-university consortium that’s advancing the mathematical foundations of ML & AI. Robotics researchers should bookmark the UW + Amazon Science Hub, which supports collaborative projects and offers an Amazon Fellowship for PhD students in robotics and AI. And scholars interested in cross-disciplinary collaborations can explore the Cross-Pacific AI Initiative (X-PAI), a long-term partnership connecting UW with NVIDIA, Amazon, and the University of Tsukuba.

Compare AI Programs at Cornell

Cornell’s Department of Computer Science offers the classic choice between a research-focused MS and a professionally focused MEng. In both cases, you have the flexibility to customize the computer science coursework to suit your interests in artificial intelligence.

• The traditional two-year MS in CS is a super-selective program designed for master’s students who are focused on AI research and willing to serve as full-time teaching assistants (TAs) throughout the program. Tuition is fully covered and all MS students receive health insurance and a stipend to cover living expenses. Instead of a final project, you’ll write a master’s thesis. Cornell undergraduates receive a strong preference for graduate admissions, so be ready to face some stiff competition.
• In contrast, the one-year MEng in Computer Science – Artificial Intelligence is a self-supported, professional program focused on practical concerns. It features a mandatory MEng project with opportunities to work on industry AI challenges or faculty research initiatives, as well as entrepreneurial electives for those who are interested in startups. Approximately 100 students are admitted each year.

What Makes Cornell a Great Artificial Intelligence School?

Cornell is a superb choice for deep-dive AI research, interdisciplinary applications, and post-graduation job opportunities in New York. The Department of Computer Science has been involved in artificial intelligence since the early 1990s, and CS faculty have a hand in a large assortment of AI labs, groups, and institutes. In particular, pay attention to what’s happening in the realms of machine learning and NLP. Then take a minute to explore the Cornell AI Initiative and its section on AI institutes & initiatives.

The university supports a number of fascinating interdisciplinary projects, including the Artificial Intelligence for Sustainability (AI4S) initiative, the Cornell Institute for Digital Agriculture (CIDA), and the Institute of Artificial Intelligence for Digital Health. Anyone thinking of a startup career should also be exploring Cornell’s Jacobs Technion–Cornell Institute, which hosts an Urban Tech Hub, a separate Health Tech Hub that leverages the strengths of Weill Cornell Medicine, and a Runway Startups program that’s designed to help entrepreneurial PhD graduates launch research-driven companies.

Compare AI Programs at Columbia

Columbia’s Department of Computer Science offers a customizable master’s degree that can be adapted to suit almost any field of AI. For the MSCS, we’ve highlighted a few pathways, but there are plenty more. On-campus MSCS students have the option to pursue a personalized pathway or thesis with faculty approval.

• The Machine Learning pathway explores machine learning fundamentals, neural networks & deep learning, and unsupervised learning.
• The Natural Language Processing track features some fascinating electrical engineering and psychology electives (e.g. models of cognition).
• The Vision, Graphics, Interaction, Robotics (VGIR) pathway offers courses in areas such as computational aspects of robotics, computer vision, HCI, and humanoid robots.

You can even earn the MSCS in an online format through the Columbia Video Network (CVN). In this situation, you’ll typically have the option to watch lectures live or the recorded version later. There are plenty of opinions about the CVN program on Reddit threads, but we recommend you speak to alumni to learn more about the pros & cons of going virtual. You should also ask the MSCS program coordinator which electives will be available and whether you can get involved in summer research projects and/or tackle an MSCS thesis.

Note: Columbia Engineering also offers a part-time Online Artificial Intelligence Certificate Program.

What Makes Columbia a Great Artificial Intelligence School?

Columbia University is located in New York City, making it an excellent choice for anyone who is eyeing AI work in the Big Apple after graduation. The Department of Computer Science is packed with faculty who have AI and machine learning research interests, but AI & computation engineering is also a strategic area of research for Columbia’s School of Engineering and Applied Science (SEAS). This School is home to unique initiatives like the NSF-funded AI Institute for Artificial and Natural Intelligence (ARNI) and the Center of AI Technology (CAIT), a joint project with Amazon.

Columbia is an especially strong pick for those who are interested in fintech and Wall Street. SEAS runs a dedicated Center for AI in Business Analytics and Financial Technology (FinTech) with a number of career-relevant partners (e.g. J.P. Morgan Chase). And in March 2024, Columbia announced a partnership with Capital One to create the Center for AI and Responsible Financial Innovation (CAIRFI). This is just the tip of the iceberg! Columbia AI has a comprehensive overview of all of the university’s AI research centers, which you can sort by topic.

Compare AI Programs at Penn

Like its closest competitor, Carnegie Mellon University, Penn has developed a large number of master’s programs in artificial intelligence. In addition to a technical MSE in an on-campus or online format, Penn offers graduate studies in robotics and even an MBA in AI.

• Professionals with a comp sci background who are seeking at traditional master’s program in AI should consider Penn’s on-campus CIS/MSE with an optional concentration in Artificial Intelligence. It consists of a computer science core—with courses in theory, systems, and machine learning—and electives in AI topics such as deep learning, advanced ML, NLP, LLMs, and more. You may even wish to complete a master’s thesis. Just check the admissions statistics section first to understand your chances of acceptance.
• Folks who are unable to live in Philadelphia can apply for the Online MSE-AI, which is also open to applicants with a computer science or computer engineering background. Thanks to its asynchronous coursework, you can work while you earn your degree. It’s a technical “soup to nuts” program that contains fundamentals in AI, ML, NLP, and data science, as well as a modest choice of electives (e.g. AI Practicum, Networked Systems, etc.). There’s no thesis in this program.

Penn is also a superb pick for C-level executives who require training in AI. The Wharton School often sits at #1 for Business School rankings and it offers an MBA with a dedicated major in Artificial Intelligence for Business. This major addresses both the technical side of AI and strategic concerns. Take a look at the Wharton AI & Analytics Initiative for more info on Wharton’s push into this field.

Or you could opt to focus on robotic systems. Penn’s General Robotics, Automation, Sensing, and Perception (GRASP) lab has developed a unique and interdisciplinary ROBO graduate program with the opportunity to customize coursework in AI & ML or computer vision and complete a thesis. The program is on the smaller side, with only about 200 students and 19 faculty members, and students are encouraged to participate in GRASP research projects and internships. In contrast, anyone involved in the field of architecture should investigate Penn’s MSD-RAS. This STEM degree explores architectural design through AI and robotic fabrication.

What Makes Penn a Great Artificial Intelligence School?

The University of Pennsylvania is an Ivy League school with instant name recognition among Northeast employers—Penn and Carnegie Mellon are Pennsylvania’s two major academic anchors in AI. The Wharton School tends to hog the headlines, but the university has technical credibility as well. See Penn AI for an overview. The Penn Advanced Research Computing Center (PARCC) is expanding. Penn Engineering supports the ASSET Center for Trustworthy AI. And computer & information science faculty are spearheading CIS research in ML & AI, NLP, HCI, algorithmic fairness, and AI for health—the section on highlighted CIS projects has more on these efforts.

We’ve already mentioned the Wharton AI & Analytics Initiative, but we wanted to highlight all of the business-heavy AI centers & labs that Wharton is now running. MBA students can take advantage of the AI & Analytics Accelerator and attend scores of AI conferences, summits, workshops, and events in Philadelphia. As a side note, the City of Brotherly Love is home to some impressive healthcare institutions & pharmaceutical companies. So it’s worth thinking about how you might leverage ASSET’s research work in AI in medicine or the Wharton Healthcare Analytics Lab to connect with potential employers.

Compare AI Programs at UC San Diego

Artificial intelligence students at UC San Diego have the option to customize a master’s degree in computer science or ECE with AI and machine learning coursework. Both on-campus programs have a research focus.

• The flagship program for AI at UC San Diego is the MS in CSE. Artificial intelligence is available as a concentration, with credits in areas such as unsupervised learning, deep generative models, ML for robotics, statistical NLP, and a whole lot more. You can customize your degree plan even further with electives and a thesis or research projects. Teaching assistantships and fellowships & scholarships are available.
• Alternatively, you could consider the MS in ECE, which features a thesis or a comprehensive exam as the final requirement. Dedicated research areas are available in Machine Learning & Data Science and Intelligent Systems, Robotics & Control. However, it’s important to note that both of these concentrations are “impacted.” That means there is a cap on the number of students admitted and admissions can be competitive.

What Makes UC San Diego a Great Artificial Intelligence School?

UC San Diego is working hard to compete with Stanford and UC Berkeley for the title of the best AI university in California, especially when it comes to advanced artificial intelligence research. In July 2024, it announced the formation of a new School of Computing, Information and Data Sciences (SCIDS), which draws on expertise from the San Diego Supercomputer Center (SDSC) and the Halicioğlu Data Science Institute (HDSI). That’s just one of the reasons why we included the ECE program in Machine Learning & Data Science in our degree listings. Potential MS students also should investigate the Department of Computer Science & Engineering’s section on AI @ CSE.

As an inside tip, UC San Diego is one of our top 3 picks for ROI. Maximum earnings for computer science graduates after 4-5 years in the job market exceeded $300k. Keep in mind, too, that HDSI has a substantial track record in AI/ML research, as well as connections to well-known government and industry partners (e.g. Lawrence Livermore National Laboratory, Deloitte, Intel, etc.). Leaning more towards robotics? HDSI is a partner in the NSF-funded The Institute for Learning-Enabled Optimization at Scale (TILOS), which is engaged in transforming chip design, robotics, and communication networks through learning-enabled optimizations.

Compare AI Programs at USC

USC has created a unique master’s degree in computer science that has AI built into its core coursework. The USC Viterbi School of Engineering also offers a number of related programs in data science with an artificial intelligence flavor.

• USC’s MSCS in AI is a custom-designed program for comp sci professionals who wish to focus immediately on artificial intelligence. You won’t be required to complete “breadth” credits in other computer science topics. Instead, you’ll be able to dive straight into foundational & theoretical courses in AI, deep learning, ML, analysis of algorithms, and web technologies. After that, you have the freedom to select three electives. Just keep in mind that the MSCS in AI doesn’t contain a thesis and is not available online.
• If you are anxious to tackle a master’s thesis and weighing a PhD, consider personalizing the general MSCS with 500-level CSCI courses in AI topics instead. The general MSCS is available online through DEN@Viterbi and is open to professional engineers.
• Alternatively, you could opt for USC Viterbi’s on-campus MS in ECE – Machine Learning and Data Science. This program is open to those with a degree in engineering or a closely related field (or equivalent skill sets). Graduates pursue roles as ML engineers, cloud engineers, software engineers, computer vision engineers, and the like. A thesis or directed research can be requested.

Speaking of data science, many of USC’s master’s programs in this field are available in on-campus and online formats through DEN@Viterbi. And once you reach the elective stage, there’s a lot of crossover with the MSCS in AI. Visit USC Data Science for more info on relevant programs.

What Makes USC a Great Artificial Intelligence School?

USC is a private research university in Los Angeles with a superb alumni network and deep pockets. USC Viterbi funds a panoply of research centers & institutes, including the USC Machine Learning Center (MaSCle) and the Center for AI in Society (CAIS). The DoD-supported Institute for Creative Technologies (ICT) is busy exploring the intersection of AI and military applications. There’s all kinds of advanced artificial intelligence research occurring within the Information Sciences Institute (ISI)—the Artificial Intelligence Division is one of the world’s largest AI research groups. And in 2023, the university announced a $1 billion investment in AI initiatives called Frontiers of Computing.

Folks who have been through the MSCS in AI program say: “prepare!” Establish what areas of AI you want to specialize in, garner some experience, reach out to relevant labs & faculty members before interviews, and expect large class sizes. USC isn’t going to hold your hand. We also recommend speaking to a student ambassador and contacting recent graduates to learn if the MSCS, the MSCS in AI, or the MS in Applied Data Science is the correct choice.

Compare AI Programs at UCLA

At UCLA, artificial intelligence graduate students can choose between customizing a traditional master’s program in computer science or opt for the professional MEng in AI from the Samueli School of Engineering.

• Anyone considering advanced research in AI should investigate UCLA’s two-year MSCS with artificial intelligence credits. It’s more selective than the Master of Engineering program, but it allows you to choose either a thesis or a capstone for your final project. The Registrar’s Office has a full list of COM SCI graduate courses with some unusual course offerings in the realms of machine learning, including work in genetics and computational genomics.
• In contrast, the professional MEng in Artificial Intelligence is expressly designed to combine the latest research with real-world applications. Electives focus on areas such as entrepreneurship, leadership, and technical project management. This on-campus degree takes just one year to complete and culminates in a summer capstone project. The program is led by Professor Guy Van den Broeck, who also directs the Statistical and Relational Artificial Intelligence (StarAI) Lab.

For robotics students, we’ve also listed the MEng in Robotics & Autonomous Systems under the direction of Professor T.C. Tsao. This is an interdisciplinary, hands-on robotics program that explores real-world applications of control systems, robot kinematics, dynamics and sensing, ML, optimization, embedded cyber-physical systems, and more. Professor Tsao leads the Mechatronics and Controls Laboratory (Maclab).

What Makes UCLA a Great Artificial Intelligence School?

The power behind artificial intelligence at UCLA comes from the Samueli School of Engineering and its highly active Department of Computer Science. Within the Department, you’ll find a large number of faculty who are busy spearheading their own AI projects & labs. The UCLA Artificial General Intelligence Lab is the most obvious one, but there are also groups devoted to ML, robot intelligence, vision, and more. We recommend a visit to Samueli’s section on Big Data, Artificial Intelligence and Machine Learning to find details on the larger institutes & centers.

UCLA is one of our top choices for anyone interested in medical & healthcare AI. The university is home to a dedicated Biomedical AI Research Lab run by the Schools of Engineering and Medicine. It supports an interdisciplinary Center for AI & SMART Health. It runs a unique Department of Computational Medicine with work in AI & genomics. It offers a hybrid Master of Data Science in Health (MDSH) at the Fielding School of Public Health. It has deep connections to UCLA Health and the UCLA Medical School’s Research Institutes. And it’s affiliated with the California Institute for Immunology and Immunotherapy (CIII) in the UCLA Research Park.

Compare AI Programs at U-M

Although U-M doesn’t offer a dedicated master’s degree in artificial intelligence, a number of its computer science, engineering & data science degrees can be modified with AI coursework.

• Looking for a research-friendly, technical qualification in AI? Consider customizing the MS in CSE or the MSE in CSE. They are practically identical, but candidates without a bachelor’s degree in engineering can only apply for the MS. These 30-credit programs include a breadth course in artificial intelligence; a slew of technical credits in ML, NLP, robotics, and HCI; and an optional thesis. Skim through the list of courses that satisfy the MS degree requirements. As an additional bonus, MS in CSE students are eligible to apply to the doctoral program.
• Do you currently work as an electrical, computer, or systems engineer? Interested in developing your skills in computational reasoning about large-scale complex engineered systems? The more relevant degree may be Michigan’s MEng in ECE with a concentration in DS/ML or autonomous systems. This one-year degree is designed to be a practical program, with coursework in “soft” areas like project management and entrepreneurship and an optional summer internship. You can compare the DS/ML concentration in the MEng in ECE side-by-side with U-M’s Master of Science in Data Science (MDS).

On that note, robotics students should stand the MEng in ECE up against the MS in Robotics from Michigan Robotics. The MS program is much more focused on actual robots, with in-depth coursework in sensing, reasoning, and human-robot interaction.

What Makes U-M a Great Artificial Intelligence School?

In addition to posting millions in annual AI research expenditures, U-M is located in Ann Arbor, which is a well-known hub of R&D in areas such as advanced automotive & mobility applications. U-M’s Computer Science and Engineering (CSE) Division supports a dedicated AI Lab at U-M, additional AI-affliated centers in health & bioinformatics, deep-dive AI research projects, scores of PhD in AI students, and a diverse range of faculty members. You’ll notice Ford, the Toyota Research Institute, and Forvia Hella in the AI Lab’s list of industrial partners. It’s also worth pointing out that there are a large number of AI women professors at U-M.

For more on Toyota’s work with U-M, visit the Toyota Research Institute (TRI)/U-M Partnership. For more on autonomy & robotics, check out Michigan Robotics, the Ford Motor Company Robotics Building, M-Air Net, and Mcity—a purpose-built connected and automated vehicle test facility. As an AI graduate student at U-M, you can also get involved in work at the Michigan Institute for Data & AI in Society (MIDAS)—see the list of funded research projects for more on its efforts. Or you could consider commercializing your discoveries. A number of CSE projects, including AI initiatives, have lead to startups through U-M’s Innovation Partnerships office.

Compare AI Programs at JHU

JHU offers an extensive range of master’s degrees in artificial intelligence, including traditional computer science programs, online AI degrees for working professionals, and business-focused qualifications in AI.

• Research-oriented students should prioritize the on-campus MSE in Computer Science, which includes approved credits in artificial intelligence coursework (e.g. advanced machine learning) or a concentration in Human Language Technology (HLT). The HLT pathway is jointly administered with the Center for Language and Speech Processing (CLSP) and includes even more opportunities to specialize (e.g. automatic speech recognition).
• Online students at JHU have a choice between the MSCS or the MSAI. The Online MSCS features a focus area in AI and a capstone project. Take a look at MSCS student publications & presentations to see how fellow students are applying their research. The alternative is the Online MSAI—examine the course list to learn if it suits your level of expertise. There are scores of advanced AI electives on offer (e.g. evolutionary and swarm intelligence, deep neural networks, etc.), as well as courses on the engineering side (e.g. building & training LLMs, UAV systems & control, etc.).

Anyone involved in corporate AI applications can investigate the Carey Business School’s 12-month MS in Information Systems and AI for Business, which is also offered in a part-time, hybrid format. This contains courses in business foundations (e.g. leadership), common corporate AI tools (e.g. machine learning), business analytics, and project management.

Engineers who wish to focus on hands-on robotics work can pursue the MSE in Mechanical Engineering – Robotics, Systems Modeling, Dynamics, and Control, which offers research opportunities in the Laboratory for Computational Sensing and Robotics (LCSR) and the Hopkins Extreme Materials Institute (HEMI).

What Makes JHU a Great Artificial Intelligence School?

In the past few years, Johns Hopkins University has been consolidating its AI centers into a centralized, multi-billion-dollar AI infrastructure. A lot of this work is being done by the Whiting School of Engineering, which oversees most of the programs in our list. Whiting supports a dedicated Johns Hopkins Data Science and AI Institute (DSAI) that is collaborating on projects with the School of Medicine, Bloomberg School of Public Health, and School of Government and Policy. View the institute’s list of AI-related centers & institutes for the full spectrum of AI research possibilities—including NLP work at the CLSP and the AI2AI – JHU + Amazon Initiative for Interactive AI.

We particularly wish to flag JHU’s advancements in autonomy and health AI. The Institute for Assured Autonomy (IAA) and the Applied Physics Laboratory (APL) are the places to go for info on JHU’s advancements in AI, ML and autonomy and robotics. Healthcare AI professionals can investigate the Artificial Intelligence & Technology Collaboratory for Aging Research (JH AITC), the multi-institution Cancer AI Alliance, and ML and AI research within the Malone Center for Engineering in Healthcare. JHU also offers a highly ranked & regarded MS in Bioinformatics.

Compare AI Programs at UT Austin

UT Austin offers AI-related degree programs in computer science, an unusual robotics certification, and a famously affordable online MSAI.

• If you’re pursuing a research path, ask the program coordinator how you can customize the on-campus, two-year MSCS to match your specific interests in AI. The MSCS is explicitly designed to lead to a PhD or academic & industry research roles. You can opt for a thesis or a coursework-only plan of study.
• If you’re currently working, you can compare the Online MSAI with the Online MSCS or the Online MSDS. All are priced at $10,000 + fees. The only required course in the Online MSAI is Ethics in AI; the remaining nine courses are AI electives. There are foundational credits (e.g. ML) as well as more advanced topics. However, there’s no final capstone project. In contrast, the Online MSCS features mandatory computer science coursework in theory and systems.

UT Austin also offers a unique Graduate Portfolio Program in Robotics. This allows graduate students to receive a “Certification of Expertise” distinction on their existing master’s or doctoral degree transcript. To earn this certification, students must complete 12 credit hours in robotics and attend & present at the Texas Robotics Portfolio Research Seminar, organized by Texas Robotics.

What Makes UT Austin a Great Artificial Intelligence School?

Typically regarded as the best university for AI in Texas, UT Austin is known for having high technical standards, plenty of research funding, and a lot of grunt. The Texas Advanced Computing Center (TACC) powers many of the university’s research projects. See Texas AI for an overview of its efforts, then visit the Department of Computer Science’s Artificial Intelligence Research section for details on faculty strengths. The Department is home to 15+ labs, institutes, and research groups in AI and robotics, including the NSF-funded TRIPODS, Texas Robotics, and—the granddaddy of them all—the Laboratory for Artificial Intelligence.

In particular, on-campus MSCS students should bookmark the Machine Learning Laboratory. This oversees efforts such as TRIPODS, the NSF-backed Institute for Foundations of Machine Learning (IFML), and the Center for Generative AI’s work in biosciences, health care, computer vision, and NLP. You should have no trouble finding opportunities to expand your career horizons! For more perspectives on the Online MSAI, talk to alumni. Folks say it’s more challenging and heavier on theory than some of the other virtual programs in our rankings.

Compare AI Programs at NYU

Artificial intelligence students at NYU can choose between a master’s program in computer science, an Online MS in Emerging Technologies, or a master’s in a closely related field. NYU has compiled a helpful list of AI-relevant graduate programs— including data science, bioinformatics & PhD opportunities—that may apply to your career situation.

• Those who are keen to study theoretical concepts and specific technologies should opt for the on-campus MSCS and customize the plan of study with AI credits. You’ll be able to select relevant courses for the core requirements, electives and the capstone. A thesis option is available.
• Those who can’t afford to live in NYC can apply for the flexible Online MS in Emerging Technologies with an ML & AI concentration—there’s a lot of crossover in the coursework with the MSCS. This program is also offered in an in-person format.

New York residents should compare the Robotics concentration in the on-campus MS in Emerging Technologies with Tandon’s hands-on MS in Mechatronics and Robotics. As the title suggests, the mechatronics program builds on mechanical engineering principles and explores areas such as assistive mechatronic and robotic technologies, mobile robotics, and microrobotics.

To give you the widest perspective on New York University’s offerings, we’ve listed some of the AI-adjacent options. For example, at NYU Stern, business folks can explore the cohort-based MSBAi program. It features in-person class sessions, a team-based capstone project, and a blend of credits in analytics and AI applications.

What Makes NYU a Great Artificial Intelligence School?

With Cornell and Columbia, NYU forms the third pillar of top-tier Carnegie R1 institutions in New York that excel in artificial intelligence research. For a quick summary, explore ai@nyu within the Courant Institute of Mathematical Sciences (CIMS). Then take a minute to investigate the Center for Data Science (CIDS) and the Tandon School of Engineering’s list of AI-related research centers and robotics & embodied intelligence projects. The robotics section highlights Tandon’s vertically integrated projects (VIP) and relevant robotics research centers & labs.

We’re flagging NYU as a strong pick for urban AI. Within NYU’s Center for Urban Science + Progress (CUSP) you’ll find the Machine Learning for Good Laboratory and AI tools that tackle critical urban challenges. Over at C2SMARTER, you’ll also discover AI solutions to transform urban mobility systems. NYU is also a great choice for altruists. Like Columbia and Cornell, NYU is part of the Empire AI consortium, a partnership between seven New York research institutions to advance AI projects for the public good. Meanwhile, Tandon’s Center for Responsible AI is shaping policy and socio-technical research through collaborations with global partners.

Compare AI Programs at UW-Madison

UW-Madison has developed two master’s degrees for artificial intelligence graduate students: a traditional, two-year MS in Computer Science, which is founded on research, and a more flexible professional program. Both on-campus degrees feature opportunities to specialize in AI.

• The research-focused CS MS comes with funding opportunities in the form of teaching assistantships, research assistantships, and graduate fellowships. As a traditional CS MS student, you’ll be expected to select a thesis or project report for your final course. And you’ll be encouraged to apply for internships. Previous students have worked for companies such as PayPal, Amazon, Google, Fetch, Roku, Qualcomm, and the like.
• The on-campus PMP is a self-funded degree. You will still have the option to tackle a thesis or project report, but you may wish to stick with coursework-only. The graduate guide has all the details on degree requirements and a list of current computer science courses, including fascinating credits in the realm of bioinformatics. We reference this because UW-Madison operates a Computation and Informatics in Biology and Medicine (CIBM) training program. However, you always can stick to more conventional realms like ML and deep learning.

For the electrical & computer engineers among our readers, we’ve also listed the MS ECE – MLSP. This degree features coursework in machine learning, signal processing, artificial neural networks, and more. It culminates in a hands-on project and/or internship.

What Makes UW-Madison a Great Artificial Intelligence School?

UW-Madison is the flagship campus of the University of Wisconsin system and an up-and-comer among AI academic institutions. In 2024, the university announced the Research, Innovation and Scholarly Excellence (RISE) Initiative, with a special interest in RISE-AI. This push for artificial intelligence glory includes a $15M grant from the Wisconsin Alumni Research Foundation (WARF) to encourage human investment in AI and plans to recruit 50 faculty in AI. On the research front, the Data Science Institute (DSI) is overseeing the RISE-AI Collaboration HQ and working to integrate new research partnerships into existing AI communities & efforts.

Put UW-Madison on your shortlist if you’re interested in agtech. The DSI has multiple active research projects in agricultural data science and UW-Madison professors are busy investigating smart foodsheds and digital agriculture projects within ICICLE. We’d also recommend it for edge computing. The School of Computer, Data & Information Sciences (CDIS) is overseeing edge computing graduate students in the N+1 Institute. Data science faculty are working with Ohio State University to develop new AI tools & techniques for wireless networks through AI-EDGE. And CS faculty are helping Duke University improve edge computing and next-gen networks at Athena.

Compare AI Programs at UMD

UMD offers a healthy number of technical graduate programs in artificial intelligence & machine learning, including a dedicated MS in AI.

• Research students can apply for the traditional two-year, on-campus MS in CS with a thesis or non-thesis option (e.g. scholarly paper). There should be plenty of room to customize your curriculum with coursework in artificial intelligence, ML, deep learning, NLP, and/or robotics. You may also be able to fund your study through fellowships, as well as teaching (TA), research (RA), and administrative assistantships (AA).
• The practical alternative to the MS in CS is the MS in AI, which features evening classes for working professionals. This program is offered through UMD’s Science Academy, in partnership with the Artificial Intelligence Interdisciplinary Institute at Maryland. It’s completely devoted to artificial intelligence, with mandatory courses in areas like computing systems for AI, ML, and safe & trustworthy AI, as well as electives in sub-fields such as AI for engineering, NLP, and cloud computing.
• Machine learning lovers should compare the MS in AI with the MS in Applied Machine Learning. It also features evening classes, no thesis, and the choice of a full-time or part-time plan of study. The core is concerned with ML, optimization, and data science, but—just like the MS in AI—you can supplement the curriculum with electives in areas like computer vision, deep learning, and robotics.

Although the MS in AI and MS in Applied ML have robotics credits, we’d direct robotics students toward UMD’s interdisciplinary MEng in Robotics, which has been endorsed by the ARM Institute. It features core courses in autonomous robots, robot modeling, and the control of robotic systems and electives in both robotics programming and unique sub-fields (e.g. rehabilitation robotics, underwater robot perception, etc.).

What Makes UMD a Great Artificial Intelligence School?

Like Johns Hopkins University, UMD benefits from being strategically positioned near Washington DC and DNA Valley—that gives it an edge in defense & healthcare AI. In April 2024, UMD announced the launch of the Artificial Intelligence Interdisciplinary Institute at Maryland (AIM), with plans to invest $100M+ into AI initiatives. AIM has provided a helpful list of AI-related research centers, including the University of Maryland Institute for Health Computing (UM-IHC) and the Industrial AI (IAI) Center. UMD also serves as the head of the NSF Institute for Trustworthy AI in Law & Society (TRAILS).

Thinking about the MS in CS? Visit the Department of Computer Science’s section on AI & robotics and browse through the faculty profiles under each specialty. Defense & cyber students should bookmark the Applied Research Laboratory for Intelligence and Security (ARLIS). It has links to the Department of Defense and an active interest in intelligent human-machine systems. Autonomous systems and robotics students can explore the GAMMA lab (e.g. embodied AI), the Center for Automotive Research (e.g. computer vision), ArtIAMAS, and the Maryland Robotics Center.

Compare AI Programs at UChicago

UChicago offers a master’s in computer science with a specialization in AI or HPC; an MBA in Applied AI; and an MEng that allows engineers to focus on AI & computation for materials.

• Folks who wish to study in Chicago and concentrate on computer science should opt for the MS in Computer Science, which is also known as the Masters Program in Computer Science (MPCS). This can be pursued on a full-time or part-time basis (15-24 months). Along with core courses in programming, theory & systems, MPCS students complete courses in AI & ML, advanced AI courses & electives in sub-fields (e.g. NLP), and an internship. There’s also an optional practicum.
• Engineers who aspire to careers in molecular engineering, materials science & related fields can pursue the Master of Engineering – AI/Computation for Materials from the Pritzker School of Molecular Engineering. This master’s degree explores the simulation, design & engineering of materials at scale. Within the AI track, there are plenty of electives in deep learning, machine learning, bioinformatics, Python, and more.
• Aspiring C-level executives should investigate the MBA in Applied AI from Chicago Booth. Booth is often ranked in the top 5 of Best Business Schools in the USA. The AI concentration is only three courses, but it will allow you to mix and match between technical credits (e.g. Machine Learning in Finance) and more business-focused AI training.

If none of these programs feel like the right fit, we recommend you consider programs from UChicago’s Data Science Institute (DSI) and Committee on Data Science (CODAS), including the on-campus and online Master of Science in Applied Data Science and the separate Master of Science in Data Science (MSDS).

What Makes UChicago a Great Artificial Intelligence School?

Located in a city that’s home to multiple Fortune 500 headquarters, UChicago is an excellent Midwest university for artificial intelligence studies. We’ve already mentioned the DSI, but take a minute to explore its AI research initiatives in AI/science, AI for climate, novel intelligence, and data ecology. In 2025, the DSI announced a new partnership with Apollo Care that’s focus on healthcare AI. And it’s collaborating with Google & UChicago Computer Science on AI security research. See the DSI list of industry partners. MEng students may also wish to learn more about UChicago’s work with Argonne National Laboratory (ANL) and ANL’s Polybot—the Center for Nanoscale Materials.

MBA in Applied AI students should bookmark Chicago Booth’s Center for Applied Artificial Intelligence and its research initiatives. The Center hosts numerous networking events. We’re also intrigued by UChicago’s moves to launch early-stage startups through Alchemist Accelerator, a deep tech accelerator at the Polsky Center for Enterpreneurship & Innovation. This accelerator supports new ventures in quantum, AI, cleantech, robotics, and more.

Compare AI Programs at Texas A&M

At Texas A&M, artificial intelligence graduate students can consider research-focused and professional programs in computer science, a dedicated MS in AI, and two online master’s degrees. All of these programs are offered by the Department of Computer Science and Engineering and all have a technical core.

• If you wish to focus immediately on AI, take a look at Texas A&M’s MS-AI with a thesis or non-thesis pathway—you can turn it into a research degree or a coursework-only program. All MS-AI students are expected to complete two core courses in AI and ML before choosing electives in topics such as deep learning, AI robotics, NLP, intelligent agents, supercomputing, and more. The virtual version is the Online MS-AI (non-thesis only).
• For comp sci research lovers, the best choice is Texas A&M’s on-campus MSCS with a mandatory thesis. MSCS students can choose to focus on an AI research area and select relevant credits in artificial intelligence and/or robotics. Search for CSCE in the course search tool for full descriptions. This program can serve as an entry point to the PhD.
• Professionals should also investigate the coursework-only MCS. This has a similar structure to the MSCS, but there is no thesis, project, or final exam. MCS students must take three CSCE breadth courses in theory, systems, and software, but there’s plenty of room to customize the degree with AI coursework. This program is also available as an Online MCS.

Finally, we wish to mention the on-campus, interdisciplinary Master of Science in Data Science (MSDS). Although the core of the program is focused on data science methods, you can choose six electives from CSCE & ECE courses, including all kinds of options in AI & ML.

Note: Texas A&M also offers an Online Artificial Intelligence & Machine Learning Certificate for working professionals.

What Makes Texas A&M a Great Artificial Intelligence School?

Texas A&M-College Station is the flagship campus of the Texas A&M system, a Carnegie R1 university, and a school with strengths in AI engineering, agriculture, and defense. We’ve already mentioned the AI research work within the Department of Computer Science and Engineering—including HPC and robotics labs—but this is just the beginning. The Texas A&M Institute of Data Science (TAMIDS) funds sector-specific AI-related research & labs and is heading up the Research in Artificial Intelligence for Science and Engineering (RAISE) initiative. Pay especial attention to TAMIDS’s work in agtech and its list of funded AI projects.

Once you’re at Texas A&M, you can take advantage of its computing resources. In 2025, the Texas A&M system announced a $45M investment to acquire a NVIDIA DGX SuperPOD, one of the most powerful supercomputing systems at any university in North America. Folks with an interest in defense R&D and autonomous & robotics research may also wish to read up on the Bush Combat Development Complex (BCDC) on the RELLIS campus near Bryan. BCDC operates test & innovation facilities in AI areas such as autonomy and works with federal defense agencies & contractors. In 2025, BCDC and DARPA paired up to deploy autonomous helicopters for wildfire response.

Compare AI Programs at Princeton

Graduate students who wish to specialize in artificial intelligence at Princeton can customize an MEng or MSE from the Department of Computer Science. Both on-campus degrees are fully funded—master’s students usually receive a teaching assistantship (TA) with a stipend.

• The two-year MSE is designed for research-oriented students. It features three core courses, three electives, and a mandatory thesis. View the Department of Computer Science’s course schedule to read full descriptions for COS courses. There are plenty of options in AI.
• The two-year, coursework-only MEng is very similar to the MSE, but it includes an additional two electives in place of a thesis (eight courses in total).

Make no mistake—these are research-focused master’s degrees with advanced coursework in artificial intelligence. Because they are fully funded, admissions will also be highly competitive.

Note: MSE and MEng students can also pursue a Graduate Certificate Program in Statistics and Machine Learning from the Center for Statistics and Machine Learning.

What Makes Princeton a Great Artificial Intelligence School?

Princeton is an excellent choice for work in deep theory and cutting-edge research in artificial intelligence. To get a handle on this Ivy League university’s strengths, start by exploring the Department of Computer Science’s AI & ML research labs and AI at Princeton. Here you can learn more about the Princeton Laboratory for Artificial Intelligence (AI Lab), the Lab’s seed grant program, Princeton’s investment in a cluster of 300 NVIDIA H100 GPUs, industry partnerships in the NJ AI Hub, and the university’s AI-affiliated units & centers.

While you’re in research mode, we suggest you check out Princeton Language and Intelligence (PLI), which is dedicated to building a foundational understanding of large-scale AI models, and Natural and Artificial Minds (NAM), which is reshaping theory-driven research in cognitive science. Princeton even supports major theoretical partnerships such as Google DeepMind Princeton, which is exploring the foundations of ML. For its work in applied AI, take a look at Princeton Precision Health (PPH) and AI for Accelerating Invention, which is using AI & ML tools to revolutionize engineering design and fabrication.

Compare AI Programs at UMass Amherst

The most relevant graduate program in artificial intelligence at UMass Amherst is the MS ECE, which is tailored toward electrical & computer engineers who wish to explore AI-related systems & methods.

• The two-year MS ECE from the Electrical and Computer Engineering (ECE) Department at UMass Amherst is available in a thesis or non-thesis pathway. Thesis students must complete a minimum of seven graduate courses and nine thesis credits. Non-thesis students complete ten courses.
• If you choose to pursue an AI and Machine Learning Systems concentration in the MS ECE, you must tackle five courses in AI topics. These credits revolve around engineering areas such as ML for engineers, applied ML for IoT, hardware design for ML systems, AI-based wireless network design, neural networks, and more.

Coming from a computer science background? UMass Amherst also offers an on-campus MSCS with a concentration in data science, a Hybrid MSCS, and an Online MSCS. These degrees are less AI-focused than the MS ECE, but they have a mandatory AI core requirement. And you can customize the program with relevant electives. Data science lovers can opt for the Master of Science in Data Analytics and Computational Social Science (MS in DACSS).

What Makes UMass Amherst a Great Artificial Intelligence School?

Although it doesn’t have the instant name recognition of MIT or Harvard, UMass Amherst is a sturdy public university in Massachusetts with a growing reputation in the intersection of artificial intelligence with life sciences and robotics. AI at UMass has a general overview of the university’s AI research initiatives, but the Manning College of Information & Computer Sciences (CICS) has a much more targeted list of AI research centers & labs, including a solid number in robotics & autonomous systems. If you’re leaning toward data science, be sure to visit the Center for Data Science and Artificial Intelligence—MS students are eligible for programs such as Data Science for the Common Good (DS4CG)—and ask about opportunities with its industry partners.

You can get a broad sense of UMass Amherst’s strengths in life sciences by investigating the Institute for Applied Life Sciences (IALS) and its graduate student research assistantship opportunities, and the NIH/NIA-funded Massachusetts AI and Technology Center for Connected Care in Aging and Alzheimer’s Disease (MassAITC), with its work in AI-enhanced tech. Massachusetts is a well-known hub of robotics, so keep in mind that you can also customize your degree with a large number of robotics courses. A quick stop at Robotics@UMass Amherst will tell you all you need to know about robotics labs, research, and faculty members. We’re especially interested in the Robotics for Human Health and Mobility research theme within the IALS’s Center for Personalized Health Monitoring.

Compare AI Programs at UC Irvine

Graduate students who wish to specialize in artificial intelligence at UC Irvine can customize one of the university’s master’s programs in computer science or choose a graduate AI degree that’s designed for working scientists.

• The research-focused MSCS consists of 47 units—four core courses, seven elective courses, and a seminar in computer science research. You can opt to substitute two elective courses for a master’s thesis. COMPSCI courses are listed in the General Catalogue. You can explore areas such as neural networks & deep learning, deep generative models, AI in biology & medicine, and more.
• The professional alternative to the MSCS is the MCS—this full-time computer science degree features project-based learning and industry collaborations. In addition to containing core credits in computer science, the curriculum features six electives, a practicum or individual study, an optional summer internship, and a capstone project. You’ll be able to select some AI & ML-related electives, but the MCS doesn’t dive as deep as the MSCS.

Alternatively, you could investigate UC Irvine’s professional Master of Data Science (MDS), which will give you training in machine learning & algorithms. This program is available in a full-time or part-time format. Like the MCS, it also includes a capstone project with an industry partner.

And then there’s the new Master of Applied AI for Science from the School of Physical Sciences. As the title suggests, this 9-month degree is aimed at professionals with a background in physical or biological sciences. The curriculum features training in Python and methods such as deep neural networks, deep learning, and software engineering. You’ll also build a portfolio through hands-on projects.

What Makes UC Irvine a Great Artificial Intelligence School?

UC Irvine is a mid-tier player in artificial intelligence in California. It can’t match Stanford and UC Berkeley for research dollars & reputation, but it is part of the UC system and it’s an intriguing choice for ML work. To get a grip on possibilities, start with the Donald Bren School of Information & Computer Sciences (ICS) and its AI faculty member profiles. In 2025, SAP SE gifted $2M to ICS to establish a Hasso Plattner Endowed Chair in AI and expand the AI curriculum. Then check out this list of the School’s AI institutes & centers, including the Center for Machine Learning and Intelligent Systems (CML) and the HPI Research Center in Machine Learning and Data Science at UCI.

Or you could focus on interdisciplinary collaborations. For instance, any scientists interested in UC Irvine’s Master of Applied AI should also be connecting with faculty members within the AI in Science Institute (AISI). Professionals with a stake in healthcare AI can get involved with UC Irvine School of Medicine’s Center for Applied Artificial Intelligence Research (A²IR). And those with an especial interest in the legal & social implications of AI can explore the Irvine Initiative in AI, Law, and Society. PhD students serve as fellows.

Compare AI Programs at Purdue

Purdue offers an online master’s program in artificial intelligence with a technical or management concentration. Research-focused graduate students can also consider customizing a standard master’s degree in computer science.

• The most targeted program is the Online MSAI with a technical or non-technical major. The AI & Machine Learning is the technical major. It features one required course in AI fundamentals, deeper dives into AI and data mining, and three electives. Be sure to read through the course list—there are a number of unique topics, including Adversial Techniques in AI and AI in Thermal Systems.
• If you’d prefer an in-person program, the MSCS from the Department of Computer Science is available in a thesis or non-thesis option. It doesn’t feature a lot of advanced AI coursework, but it will allow you to cover the greatest hits—AI, statistical ML, NLP, and foundations of deep learning. You can also add courses in algorithms & bioinformatics.

Managers, business analysts, and policy makers who don’t have a programming or coding background can consider the AI Management & Policy in the Online MSAI. This explores the use of AI in various sectors and ideas around project management, risk management, and leadership.

For our robotics & engineering readers, we’ve also listed professional master’s programs in Autonomous and Connected Systems (ACS) from Purdue’s College of Engineering. Have a look at the on-campus degree requirements and sample course plans to get a gauge on the relevance of each major. The online programs have a slightly different plan of study, so it’s worth comparing curricula.

What Makes Purdue a Great Artificial Intelligence School?

Purdue is one of the biggest STEM-focused universities in the Midwest, with well-established strengths in engineering—AI employers will know the name! It’s also a Carnegie R1 school that exceeded $1B in total research expenditures in 2025. For an overview of AI initiatives, visit Purdue Computes. Purdue has a major interest in semiconductors—it’s the lead academic digital twin center for the Semiconductor Manufacturing and Advanced Research with Twins (SMART) USA Institute. It funds the Purdue Quantum Science and Engineering Institute (PQSEI). And it’s now working with Eli Lilly on a $250M Lilly-Purdue 360 Initiative to advance pharmaceutical discoveries through tech & AI.

Unlike more theoretical schools in our rankings, Purdue is especially invested in hardware & applied AI. In 2023, the university launched the country’s first Institute of Physical AI (IPAI), which oversees 20+ affiliated centers and labs in everything from robotics & autonomy to smart manufacturing. For anyone eyeing the autonomy major, we also want to highlight the Center on AI for Digital, Autonomous and Augmented Aviation (AIDA³ ), which was co-founded with Windracers. If you’re thinking of local job opportunities, be sure to check out the companies at Purdue Research Park. To take just one example, SK hynix is building an impressive AI semiconductor facility and R&D center there.

Compare AI Programs at ASU

ASU has two major strands of graduate programs in artificial intelligence—technical master’s programs in AI and robotics from the Fulton Schools of Engineering and business-focused MS and MBA degrees from W.P. Carey School of Business.

• Professionals with an engineering bent can explore the MS in AI Engineering, which is available in discipline-specific concentrations such as: computing sciences, software engineering, electrical engineering, mechanical engineering, human-centered AI, operations & decision science, materials science, and robotics. You’ll be able to choose an applied project, thesis, and/or a portfolio for your culminating experience—check each degree for details.
• Robotics students should compare the curriculum for the MS in Artificial Intelligence Engineering – Robotics with the MS in Robotics & Autonomous Systems (RAS). The RAS degree features concentrations in a number of engineering fields, including biomedical engineering, and a dedicated concentration in AI developed by the School of Computing and Augmented Intelligence (SCAI).

Plus there are the corporate options. The W.P. Carey School of Business offers its flexible MS-AIB in an on-campus format (Tempe or LA) and a 100% online format. The curriculum is designed to prep business professionals for AI leadership positions and contains foundational courses in AI tools & methods. You can compare this program to the full-time MBA in Artificial Intelligence. Required coursework in the MBA in AI concentration includes training in Python, machine learning, business data visualization, and AI & business applications.

What Makes ASU a Great Artificial Intelligence School?

ASU isn’t a top-tier AI research university, but it has a respectable reputation for computer science in Arizona and its known for delivering solid online programs. The first port of call for potential MS in AI Engineering applicants should be the School of Computing and Augmented Intelligence (SCAI)—this has sections on AI-related research centers & labs and their faculty leaders. Anyone considering the MS-AIB or MBA might wish to bookmark the Center for AI and Data Analytics (AIDA) for Business and Society and explore its research labs & units in areas like healthcare, finance, blockchain technologies, and sustainability.

ASU is also an intriguing pick for anyone thinking of defense & security applications. Within the Global Security Initiative (GSI), you’ll find the Center for Human, Artificial Intelligence, and Robot Teaming (CHART), which is exploring applications in human–AI-robot teaming, autonomous vehicles, logistics defense operations, and more. We’re also curious about the work of the Center on Information and Narrative Complexity (CINC) in AI-driven information manipulation. See the section on Defense Technology & Innovation for more on ASU’s drive to strengthen national security and meet military and defense needs.

Compare AI Programs at BU

BU offers a dedicated master’s degree in artificial intelligence through the Graduate School of Arts & Sciences; a robotics-focused master’s program through the College of Enginering; and AI-related graduate programs through its Metropolitan College (MET).

• The MS in AI is the most focused artificial intelligence program at BU. It’s open to applicants with a computing background who are aiming for AI engineer-type roles or considering a PhD in Computer Science. All of the core courses revolve around AI topics (e.g. AI, ML, NLP, etc.) and you can select electives to match. There’s even an optional thesis pathway.
• For robotics students, there’s the MS in Robotics & Autonomous Systems, which combines high-level theory with hands-on projects in industry or research. Exceptional applicants from diverse backgrounds are eligilble for a fully-funded Amazon Robotics Day One Fellowship, which includes the chance to take part in the Amazon Robotics internship program.

If you’d like to expand your horizons further, you can compare the MS in AI with closely related programs such as BU’s Master of Science in Data Science (MSDS) and Master of Science in Electrical and Computer Engineering (MS in ECE). There’s wiggle room to customize either program with artificial intelligence & machine learning coursework.

Or you could consider a number of offerings from BU’s Metropolitan College (BU MET)—this is a private college within BU that offers work-friendly programs for adults & professionals. BU MET offers an on-campus MSCS – AI & Machine Learning (part-time or full-time) and an MS in Applied Data Analytics – AI & Machine Learning that can be earned on-campus or online.

What Makes BU a Great Artificial Intelligence School?

In the past few years, BU has built a track record as one of Massachusetts’s more prominent academic players in artificial intelligence. Though it’s not on par with MIT or Harvard, it’s one of the anchor universities for the Massachusetts AI Hub. And it’s currently consolidating its efforts. Within the Hariri Institute for Computing & Computational Science & Engineering, you’ll discover 10 AI centers & initiatives, including the AI Research Initiative, the Digital Health Initiative, the Center for Computational Science (CCS), and the Red Hat Collaboratory, an industry–academic partnership.

Massachusetts has a thriving robotics community, but it pays to make career connections early. If you’re consider in the MS in Robotics & Autonomous Systems, visit the Robotics & Autonomous Systems Teaching and Innovation Center (RASTIC). This center has a number of valuable industry partners. BU is also involved in some unusual healthcare collaborations. For example, the Biothreats Emergence, Analysis and Communications Network (BEACON) in the Center on Emerging Infectious Diseases (CEID) is deploying AI to run an open-source global surveillance platform for public health professionals.