| Top No-GRE AI Master’s Programs in 2026 (Alphabetical Order) | ||
|---|---|---|
| GRE Policy | University | Program |
| Optional | Boston University | MS in Artificial Intelligence |
| Optional | Duke University | MEng in AI for Product Innovation |
| Optional | Illinois Tech | MS in Artificial Intelligence |
| Test-Free | Johns Hopkins | MS in Artificial Intelligence |
| Test-Free | Maryville University | MS in Artificial Intelligence |
| Optional | Northwestern | MS in Artificial Intelligence |
| Test-Free | Penn State | Master of Artificial Intelligence |
| Optional | University of Pennsylvania | MSE in AI Online |
| Optional | University of San Diego | MS in Applied AI |
| Optional | UT Austin | MS in Artificial Intelligence |
Boston University – Master of Science in Artificial Intelligence
BU’s MSAI curriculum focuses on the technical skills to build and deploy modern AI tools. You start with essentials like machine learning, natural language processing, and image computing. You can then customize the degree with marketable electives like deep learning, digital video processing, and applied cryptography. The program culminates with a research-heavy thesis or comprehensive applied software capstone.
The admissions process prioritizes candidates with a software development background. While a CS degree is standard, the committee also values proficiency in Python or C++. The GRE is optional, so you decide if including your scores will bolster your application. Of those who do submit a GRE, the average percentiles of admitted students are 60% for Verbal and 80% for Quantitative.
Duke University – Master of Engineering in AI for Product Innovation
Duke’s AIPI teaches you how to turn ML models into market-ready software by merging technical engineering and product strategy. Students take applied courses in hot domains like deep learning, MLOps, and data analytics, alongside business management training. You then apply these skills through a required internship and a semester-long capstone building full-stack AI solutions.
The admissions process focuses on your technical background and communication skills. In lieu of the GRE, the committee looks at three short-answer essays, your technical resume, and a video introduction. The program requires a strong foundation in calculus and programming (preferably Python) and doesn’t enforce a minimum GPA.
Illinois Institute of Technology – Artificial Intelligence (M.A.S.)
The core curriculum of IIT’s Master of Applied Science in AI covers advanced machine learning and NLP, while its massive elective catalog lets you target hot domains like computer vision, social network analysis, smart grid AI, and bioinformatics. Throughout the program, you’ll design functional AI models to prepare you for roles in business, robotics, medicine, and more.
You can enroll without a computer science background if you have a strong foundation in math and analytics. If you’re missing CS credits, you can catch up through accelerated bridge courses in computer science and programming. The GRE is optional, so only submit scores if they’ll strengthen your application.
Johns Hopkins University – Master of Science in Artificial Intelligence
JHU’s online MSAI covers essentials in algorithms, generative AI, and applied ML before letting you tailor the degree with job-ready electives like MLOps, AI for Cybersecurity, Healthcare AI, Deep Learning for Computer Vision, and Agentic AI. Developed with the university’s prestigious Applied Physics Lab, the curriculum pushes you to design, train, and deploy functional AI systems to address real-world problems.
Johns Hopkins uses a strict test-blind policy so GRE scores are not considered. The admissions review board evaluates applicants based on academic transcripts, professional experience, and analytical readiness. Students who lack certain prerequisites can take university-provided proficiency exams (with no fee for local testers) to bypass some requirements.
Maryville University – Master of Science in Artificial Intelligence
Maryville’s online AI master’s is all about learning by doing. Students wield in-demand tools like Python, R, and AWS throughout courses in deep learning, reinforcement learning, and data ethics. The degree culminates in an applied capstone where you build a fully functional AI business solution. The hands-on structure is great for developing a portfolio that validates your ability to apply technical theory to real-world problems.
The program has a test-blind policy so the committee won’t consider GRE scores. Your acceptance relies on your undergraduate transcript, resume, and a personal statement to show your technical potential. While the program doesn’t require a formal CS degree, you should be versed in math and analytical thinking to manage the technical requirements.
Northwestern University – Master of Science in AI
Northwestern’s MSAI program focuses on integrating cutting-edge AI with business workflows. Beyond core classes in AI frameworks, data science, and machine learning, students can specialize the degree with electives in emerging domains like Active Learning in Robotics, Machine Perception of Music & Audio, Advanced Computer Vision, and Law and the Governance of AI.
The GRE is optional. The admissions team does a comprehensive background review that looks for self-directed technical skill; they encourage applicants to submit links to their GitHub repositories and Stack Overflow developer profiles.
Penn State – Master of Artificial Intelligence
Penn State’s AI master’s program teaches you how to design, develop, and scale modern AI products. Delivered online via the university’s World Campus, the degree covers hot domains like NLP, Machine Vision, Deep Learning, AI Ethics, and Data-Driven Decision-Making. Students complete the sequence with a customized capstone to showcase their hard-earned AI skills and bolster their portfolio.
With a strict test-blind policy, evaluators rely on your transcripts, statement of purpose, resume, and letters of recommendation. Applicants missing formal CS classes can prove their coding readiness by submitting a technical recommendation letter detailing their professional software experience.
University of Pennsylvania – MS in Engineering in AI Online
Penn Engineering’s MSE-AI explores the technical architecture behind modern AI. The curriculum covers classical AI, NLP, generative AI, and deep learning. You also study the infrastructure that makes these models run with coursework in GPU programming, distributed systems, and statistical modeling. The program boasts a stellar ethical framework to help you anticipate and mitigate the risks of building AI tools.
The GRE is totally optional. The admissions team targets candidates with a bachelor’s in computer science, engineering, or information science. Applicnts need to provide a technical resume, personal statement, and two letters of recommendation.
University of San Diego – Master of Science in Applied AI (MS-AAI)
USD’s online master’s in applied AI teaches students to build and deploy responsible AI tools to solve real-world issues. The curriculum dives right into model construction with courses like Applied Computer Vision, NLP and GenAI, and MLOps. The program culminates in a collaborative capstone where students, instructors, and industry partners solve an active industry problem.
The GRE is optional, but evaluators strongly recommend submitting a score if your undergraduate GPA is under 2.75. Applicants missing technical requirements like calculus, Python programming, or GitHub proficiency can still get in by submitting a one-page strategy detailing how they will acquire those skills before classes start.
University of Texas at Austin – Master of Science in AI (MSAI)
UT Austin’s online MSAI delivers advanced technical training at a fraction of the cost of most graduate credentials. For $10,000 plus fees, students learn practical skills in generative modeling, convex optimization, and natural language processing. The curriculum focuses heavily on applied engineering where students design, train, and debug deep networks using PyTorch.
The admissions committee evaluates candidates on their computing background, academic history, resume, and statement of purpose. The GRE is optional and available to use to supplement your application.
