Best Online Master’s in AI Programs

An online master’s in artificial intelligence can help software developers, data professionals, engineers, technical leaders, and career changers build advanced skills in machine learning, deep learning, natural language processing, computer vision, generative AI, MLOps, and responsible AI systems.

The best programs combine rigorous technical coursework with flexible online delivery, transparent tuition, applied projects, and clear admissions guidance.

The key is choosing carefully. AI graduate programs vary widely: some are engineering-heavy, some are applied and business-focused, some emphasize machine learning theory, and others focus on product development or AI deployment.

Students should compare cost, prerequisites, GRE policy, curriculum depth, capstone options, faculty expertise, and career alignment before enrolling.

An online master’s in artificial intelligence can be worth it for students and working professionals who already have or are willing to build strong foundations in programming, math, statistics, data structures, and algorithms. It can support career movement into AI engineering, machine learning, data science, applied AI, AI product, cybersecurity automation, robotics, or research-adjacent roles.

However, the degree alone does not guarantee an AI engineer job. Outcomes depend on prior experience, portfolio strength, technical skill, domain knowledge, location, and hiring-market conditions.

Stanford HAI’s 2026 AI Index shows that AI adoption is spreading quickly, with organizational AI adoption reaching 88 percent of surveyed organizations and generative AI reaching 53 percent population adoption within three years.

The same report also notes uneven labor-market effects, including pressure on younger software developers in exposed occupations, which makes hands-on skill building and portfolio evidence especially important.

What Is an Online Master’s in Artificial Intelligence?

An online master’s in artificial intelligence is a graduate degree focused on building intelligent software systems. Students typically study machine learning, deep learning, algorithms, data science, natural language processing, computer vision, robotics, AI ethics, and AI deployment.

Compared with a certificate or bootcamp, a master’s degree is usually more comprehensive and academically rigorous. Compared with a bachelor’s degree, it is more specialized. Compared with a PhD, it is generally more career-focused and shorter, although some programs can support research preparation.

Online AI master’s courses may include recorded lectures, live sessions, coding assignments, cloud labs, exams, team projects, peer discussion, and capstones. Some programs are asynchronous, while others require scheduled online meetings.

Students should compare curriculum depth, prerequisites, faculty expertise, online support, and applied project opportunities rather than choosing based only on brand name.

Many AI master’s programs are not beginner-level. Applicants may need preparation in Python, probability, statistics, calculus, linear algebra, data structures, algorithms, and computer science fundamentals.

Tuition rates

Data from dozens of online Artificial Intelligence Master’s programs across various institutions reveals:

16 online options
Average Total Cost: $42,530.
Lowest Per-Credit Rate: $333.
Highest Per-Credit Rate: $1,818.

Best Online Master’s in Artificial Intelligence Programs for 2026

Stevens Institute of Technology
Hoboken, New Jersey
Program: Online Master's in Applied Artificial Intelligence
ARTiBA accreditation: No
Delivery method: Online & campus
Total tuition: $41,850
2026 Cost per credit: $1,395
Credits: 30
Learn more: Program details
Drexel University
Philadelphia, Pennsylvania
Program: Online Master’s in Machine Learning and Artificial Intelligence
ARTiBA accreditation: No
Delivery method: Online & campus
Total tuition: $66,645
2026 Cost per credit: $1,481
Credits: 45
Learn more: Program details
Maryville University
St. Louis, Missouri
Program: Online Master of Science in Artificial Intelligence
ARTiBA accreditation: No
Delivery method: Online
Total tuition: $28,875
2026 Cost per credit: $875
Credits: 33
Learn more: Program details
University of the Cumberlands
Williamsburg, Kentucky
Program: Online Executive Master's in Artificial Intelligence
ARTiBA accreditation: No
Delivery method: Hybrid
Total tuition: $11,005
2026 Cost per credit: $355
Credits: 31
Learn more: Program details
Rochester Institute of Technology
Rochester, New York
Program: Online Master's in Artificial Intelligence
ARTiBA accreditation: No
Delivery method: Online & campus
Total tuition: $42,090
2026 Cost per credit: $1,403
Credits: 30
Learn more: Program details
Illinois Institute of Technology
Chicago, Illinois
Program: Online Master of Artificial Intelligence
ARTiBA accreditation: No
Delivery method: Online & campus
Total tuition: $53,400
2026 Cost per credit: $1,780
Credits: 30
Learn more: Program details
Pennsylvania State University
University Park, Pennsylvania
Program: Online Master of Artificial Intelligence
ARTiBA accreditation: No
Delivery method: Online
Total tuition: $35,574
2026 Cost per credit: $1,078
Credits: 33
Learn more: Program details
University of Bridgeport
Bridgeport, Connecticut
Program: Master’s in Artificial Intelligence (AI)
ARTiBA accreditation: No
Delivery method: Online & campus
Total tuition: $36,550
2026 Cost per credit: $1,075
Credits: 34
Learn more: Program details
DePaul University
Chicago, Illinois
Program: Online Master of Science in Artificial Intelligence
ARTiBA accreditation: No
Delivery method: Online & campus
Total tuition: $86,800
2026 Cost per credit: $1,808
Credits: 48
Learn more: Program details
University of San Diego
San Diego, California
Program: Online Master of Science in Applied Artificial Intelligence
ARTiBA accreditation: No
Delivery method: Online
Total tuition: $28,950
2026 Cost per credit: $965
Credits: 30
Learn more: Program details
Johns Hopkins University
Baltimore, Maryland
Program: Online Master's in Artificial Intelligence
ARTiBA accreditation: No
Delivery method: Online
Total tuition: $54,550
2026 Cost per credit: $1,818
Credits: 30
Learn more: Program details
University of Texas at Austin
Austin, Texas
Program: Online Master’s of Artificial Intelligence
ARTiBA accreditation: No
Delivery method: Online
Total tuition: $10,000
2026 Cost per credit: $333
Credits: 30
Learn more: Program details
Duke University
Durham, North Carolina
Program: Online Masters in Applied AI for Product Innovation
ARTiBA accreditation: Yes
Delivery method: Online & campus
Total tuition: $99,000
2026 Cost per credit: $3,299
Credits: 30
Learn more: Program details
Colorado State University Global
Aurora, Colorado
Program: Online Master's in Artificial Intelligence (AI) & Machine Learning
ARTiBA accreditation: No
Delivery method: Online
Total tuition: $24,300
2026 Cost per credit: $675
Credits: 36
Learn more: Program details
University of North Texas
Denton, Texas
Program: Master of Science in Artificial Intelligence
ARTiBA accreditation: No
Delivery method: Online & campus
Total tuition: $29,224.14 in-state | $42,599.04
2026 Cost per credit: $885.88 in-state | $1,290.88 out-of-state
Credits: 33
Learn more: Program details

These rankings were compiled from data accessed in January 2026 from Integrated Post-Secondary Education Data System (IPEDS) and College Navigator (both services National Center for Education Statistics). Tuition data was pulled from individual university websites and is current as of January 2026. If available, we also use additional criteria such as accreditation or designations by outside organizations or agencies.

2025 Rankings

STEVENS INSTITUTE OF TECHNOLOGY
JOHNS HOPKINS UNIVERSITY
DUKE UNIVERSITY

Professionals with a master’s degree in AI have the potential to earn a very attractive salary due to their highly specialized skill set. Although the Bureau of Labor Statistics (BLS) does not have a separate listing for AI engineers, the median wage for computer scientists is around $145,080.

Online AI Master’s vs Computer Science, Data Science, and Machine Learning Degrees

Degree path	Best for	Main advantage	Limitation
Online MS in Artificial Intelligence	Students focused on AI systems, ML, NLP, computer vision, and applied AI	Direct AI focus	May be too specialized for students needing broader CS foundations
Online MS in Computer Science with AI/ML specialization	Software engineers and CS graduates	Broad CS foundation plus AI depth	May require stronger CS prerequisites
Online MS in Data Science	Analytics, statistics, modeling, and business data roles	Strong applied data focus	May cover less robotics, AI systems, or advanced CS
Online MS in Machine Learning	ML engineering and model development	Strong ML specialization	Narrower than CS or AI
AI certificate	Upskilling without a full degree	Faster and cheaper	Less comprehensive and may not carry degree-level value

Choose an AI master’s if your goal is to build or manage AI systems.

Choose computer science if you want broader software and systems depth.

Choose data science if your target roles center on analytics, statistics, modeling, and business data.

Choose machine learning if you want a narrower ML-focused path.

Choose a certificate if you need targeted upskilling rather than a full graduate degree.

Related Resources

Admissions Requirements and Prerequisites

Most online AI master’s programs require a bachelor’s degree, transcripts, resume, statement of purpose, and sometimes letters of recommendation. Some require the GRE, while others waive it or do not require it. Common prerequisites include:

Requirement	Why it matters
Programming experience	AI coursework often uses Python, Java, C++, or R
Python readiness	Python is widely used for machine learning, deep learning, and data science
Data structures and algorithms	Needed for efficient software and model implementation
Calculus	Important for optimization and gradient-based learning
Linear algebra	Essential for vectors, matrices, neural networks, and embeddings
Probability and statistics	Needed for modeling, inference, validation, and uncertainty
Discrete math	Useful for algorithms, logic, and computational reasoning
Prior CS coursework	Helps students handle graduate-level technical material
Work experience	Often helpful for professional and executive AI programs

Applicant Readiness Checklist

You are likely ready for an online AI master’s if you can write code, understand basic algorithms, work with data, interpret statistics, and commit time to projects beyond required coursework. You may need bridge courses if you lack programming, linear algebra, calculus, or statistics.

What You’ll Learn in an Online AI Master’s Program

Curriculum area	What students learn
Machine learning	Supervised learning, unsupervised learning, model training, validation
Deep learning	Neural networks, CNNs, RNNs, transformers
Natural language processing	Text classification, embeddings, language models
Generative AI	LLMs, prompt engineering, multimodal AI, AI-assisted workflows
Retrieval-augmented generation	Vector databases, embeddings, search, grounding, evaluation
MLOps	Deployment, monitoring, versioning, CI/CD for models
Responsible AI	Fairness, bias, transparency, explainability, governance
AI security	Adversarial attacks, model misuse, data leakage, prompt injection
Computer vision	Image classification, object detection, segmentation
Robotics or autonomous systems	Perception, planning, control, reinforcement learning
AI product development	Human-centered design, business use cases, model evaluation
Capstone or thesis	Applied project, research project, or portfolio-ready AI system

Common Courses in Online AI Master’s Programs

Course	What students usually study
Artificial Intelligence	Search, planning, reasoning, agents, knowledge representation
Machine Learning	Regression, classification, clustering, model evaluation
Deep Learning	Neural networks, transformers, CNNs, RNNs
Natural Language Processing	Language models, embeddings, text classification, sentiment analysis
Computer Vision	Image classification, object detection, segmentation
Reinforcement Learning	Agents, rewards, policy learning, decision-making
Generative AI	LLMs, multimodal models, prompting, evaluation
Large Language Models	Transformers, fine-tuning, RAG, deployment concepts
Data Mining	Pattern discovery, preprocessing, feature engineering
Statistical Learning	Model selection, probability, inference, validation
Algorithms	Complexity, optimization, graph algorithms
Responsible AI	Bias, fairness, explainability, governance
AI Security	Prompt injection, adversarial ML, data leakage, misuse risks
MLOps	Deployment, monitoring, CI/CD, model versioning
Capstone or Thesis	Applied AI project or research-focused final project

Generative AI, LLMs, RAG, and MLOps

Modern AI education should go beyond traditional machine learning theory. Students interested in applied AI engineering should look for programs that include:

Large language models
Prompt engineering
Embeddings
Vector databases
Retrieval-augmented generation
Model evaluation and benchmarking
AI agents and workflow automation
Cloud deployment
MLOps pipelines
Model monitoring
AI security risks
Responsible AI governance

A strong AI portfolio should show that a student can frame a problem, prepare data, choose a model, evaluate performance, deploy a system, monitor limitations, document risks, and communicate results to technical and nontechnical stakeholders.

Responsible AI and Governance

Responsible AI is now a core skill area, not an optional topic. AI systems can create risks related to bias, fairness, privacy, security, transparency, accountability, and misuse.

NIST’s AI Risk Management Framework identifies characteristics of trustworthy AI systems, including validity and reliability, safety, security and resilience, accountability and transparency, explainability and interpretability, privacy enhancement, and fairness with harmful bias managed.

Students comparing online AI master’s programs should look for coursework or projects covering:

Responsible AI area	Why it matters
Bias and fairness	Helps identify unequal model performance across groups
Explainability	Helps users understand why a model made a decision
Transparency	Supports documentation, auditing, and accountability
Data privacy	Reduces risk from sensitive or personal data
Human oversight	Keeps humans responsible for high-impact decisions
Model documentation	Clarifies training data, limitations, and intended use
Governance frameworks	Helps organizations manage AI risk
AI security	Addresses prompt injection, data leakage, and adversarial threats
Ethical deployment	Supports safe and responsible use in real settings

How Much Does an Online Master’s in AI Cost?

Online AI master’s tuition can range from about $10,000 at some public online programs to more than $60,000 at higher-cost private universities. The total depends on tuition per credit, total credits, required fees, software costs, cloud computing costs, and time to completion.

Cost factor	What students should check
Tuition per credit	Rates vary widely by school and program type
Total credits	Most programs require 30 to 45 credits
Fees	Online, technology, graduation, proctoring, and student fees
Cloud and software costs	AI coursework may require cloud computing or specialized tools
Employer assistance	Many working professionals use tuition reimbursement
Military/veteran benefits	Verify GI Bill, Yellow Ribbon, or military-affiliated benefits
Scholarships	Check institutional and department-level aid
Time to completion	Longer programs can increase indirect costs

Students should ask schools whether tuition estimates include all required fees. For example, CSU Global lists $675 per credit and 30 credits for its online MS in AI and Machine Learning, while the University of San Diego lists 30 units and $995 per online unit for its MS in Applied Artificial Intelligence.

Financial Aid, Employer Tuition Assistance, and Scholarships

Students in accredited graduate programs may be eligible for federal student loans by submitting the FAFSA.

Other funding options may include employer tuition reimbursement, institutional scholarships, military and veteran education benefits, department scholarships, graduate assistantships, payment plans, and professional development budgets.

Working professionals should ask their employer whether the program qualifies for reimbursement and whether course grades, annual maximums, or continued employment requirements apply.

What Jobs Can You Get With a Master’s in Artificial Intelligence?

Role	Notes
Machine learning engineer	Often requires strong software engineering and ML deployment skills
AI engineer	Competitive role; may require production ML or generative AI experience
Data scientist	Often requires statistics, modeling, SQL, Python, and business context
Applied scientist	May require research experience or advanced math
AI research scientist	Often prefers or requires a PhD for research-heavy roles
NLP engineer	Requires language modeling, text processing, evaluation, and deployment
Computer vision engineer	Requires image processing, deep learning, and model evaluation
Robotics engineer	Requires perception, planning, controls, and systems knowledge
MLOps engineer	Focuses on deployment, monitoring, infrastructure, and automation
AI product manager	Combines AI literacy with product strategy and stakeholder management
AI governance specialist	Focuses on risk, policy, documentation, and responsible AI
AI security specialist	Works on model misuse, prompt injection, adversarial ML, and data leakage
AI solutions architect	Designs AI systems for business or enterprise environments

Some roles may require prior work experience, domain expertise, publications, advanced math, security knowledge, cloud skills, or a stronger software engineering background than the degree alone provides.

AI Master’s Salary and Job Outlook

The Bureau of Labor Statistics does not have a single “AI engineer” occupation, so salary and outlook should be framed using adjacent roles.

Career path	Current BLS proxy	2024 median pay	2024–2034 outlook	Degree context
AI research scientist / computer scientist	Computer and information research scientists	$140,910	20% growth	Master’s is typical; PhD may be needed for some research roles
Data scientist / ML-focused data scientist	Data scientists	$112,590	34% growth	Bachelor’s is typical, but AI/ML graduate training can help
Software developer / AI software developer	Software developers, QA analysts, and testers	$133,080	15% growth	Bachelor’s is typical; master’s can support specialization
AI security / security automation	Information security analysts	$124,910	29% growth	Bachelor’s is typical; security experience matters
AI product or technical leadership	Computer and information systems managers	$171,200	15% growth	Usually requires experience plus technical or management depth
AI systems implementation	Computer and IT occupations overall	$105,990	Faster than average overall	Role-specific requirements vary

Salaries vary by role, location, experience, industry, technical portfolio, prior work history, and whether the job is closer to software engineering, data science, research, product management, cybersecurity, or IT leadership. BLS data should be used as occupational context, not as a guaranteed salary outcome for AI master’s graduates.

How to Build a Job-Ready AI Portfolio During Your Master’s

A strong AI portfolio should show more than a notebook with model accuracy. It should demonstrate problem framing, data quality decisions, model selection, evaluation, deployment, documentation, and limitations.

Project ideas include:

Portfolio project	What it can demonstrate
End-to-end ML model with deployment	Model training, API deployment, monitoring
LLM chatbot with RAG	Embeddings, vector search, grounding, evaluation
Computer vision classifier	Image preprocessing, CNNs, validation
NLP text analysis tool	Tokenization, embeddings, classification, explainability
Model evaluation dashboard	Metrics, error analysis, fairness checks
Responsible AI audit	Bias testing, documentation, governance thinking
AI product prototype	User needs, model behavior, UX, business value
Cloud-deployed ML API	Infrastructure, MLOps, reproducibility
MLOps pipeline	Versioning, CI/CD, monitoring
AI governance documentation	Risk management, model cards, intended use
Domain-specific AI project	Healthcare, finance, education, cybersecurity, operations

Students targeting AI engineering should prioritize deployed projects, not just coursework. Students targeting research should add literature reviews, experiments, and reproducible code.

Certifications That Pair Well With an AI Master’s

Goal	Useful certifications or credentials
Cloud AI	AWS, Google Cloud, or Microsoft Azure AI/cloud credentials
Data science	Databricks, SQL, Python, or analytics credentials
Machine learning engineering	Cloud ML, MLOps, and model deployment credentials
Cybersecurity and AI security	Security+, cloud security, or AI security-focused credentials
AI governance	Responsible AI, privacy, risk management, or governance training
Product or business AI	AI product management or analytics credentials

Certifications should support a specific role. They should not replace graduate coursework, portfolio projects, internships, work experience, or strong technical fundamentals.

How to Choose the Right Online AI Master’s Program

Factor	What to ask
Accreditation	Is the institution accredited? Is any programmatic accreditation relevant?
Program reputation	Is the program known for AI, CS, engineering, data science, or applied computing?
Curriculum depth	Does it include ML, deep learning, NLP, computer vision, and AI systems?
Generative AI	Are LLMs, RAG, prompt engineering, or AI agents covered?
MLOps	Does the program teach deployment, monitoring, and production ML?
Responsible AI	Are ethics, bias, fairness, governance, and AI risk included?
Capstone or thesis	Will you graduate with portfolio-ready work?
Faculty expertise	Do faculty have AI, ML, data science, or systems experience?
Online format	Is it fully online, hybrid, synchronous, asynchronous, or self-paced?
Prerequisites	Are Python, calculus, linear algebra, stats, or algorithms required?
GRE policy	Is the GRE required, optional, waived, or not accepted?
Bridge courses	Are there options for non-CS applicants?
Tuition and fees	Is the full cost transparent?
Career support	Are there career coaching, employer connections, or alumni resources?
Fit	Is the program best for engineering, research, product, leadership, or applied AI?

Application Checklist

Define your AI career goal.
Compare AI, machine learning, computer science, and data science programs.
Check prerequisites.
Review math and programming requirements.
Confirm online format.
Compare tuition and fees.
Check GRE requirements or waiver policies.
Review capstone, thesis, or project options.
Gather transcripts.
Update your resume.
Prepare a statement of purpose.
Request recommendation letters.
Ask about career support and portfolio opportunities.
Verify accreditation and program data.
Apply before priority deadlines.

Is an Online Master’s in Artificial Intelligence Worth It?

An online master’s in artificial intelligence can be worth it when the program is rigorous, affordable, flexible, and aligned with your goals. It is especially valuable for learners who already have technical foundations and want to move into AI/ML engineering, data science, applied AI, research-adjacent roles, or AI leadership.

Student type	Worth-it assessment
Software engineer seeking AI specialization	Strong fit if the program includes ML, deep learning, MLOps, and generative AI
Data professional moving into ML	Good fit if it adds algorithms, deep learning, deployment, and AI systems
Technical professional applying AI in industry	Good fit if applied projects match the student’s domain
Student preparing for research or doctoral study	Good fit if the program includes thesis or research options
Working adult needing flexibility	Good fit if the program is asynchronous or part time
Beginner without math or programming preparation	Less ideal unless bridge courses are available
Student seeking the fastest entry-level job	A bootcamp, certificate, or focused portfolio path may be faster
Student unwilling to build projects outside class	Less ideal because AI hiring often requires portfolio evidence

Frequently Asked Questions

Is an online master’s in artificial intelligence worth it?

Yes, an online master’s in artificial intelligence can be worth it for students with technical preparation who want graduate-level AI, machine learning, deep learning, generative AI, or MLOps training. It is less ideal for beginners who lack programming or math foundations.

What can you do with an online master’s in AI?

Graduates may pursue roles in machine learning engineering, AI engineering, data science, applied AI, NLP, computer vision, MLOps, AI product management, AI governance, robotics, cybersecurity automation, or AI solutions architecture.

Do I need a computer science background for an AI master’s?

Not always, but most programs expect technical readiness. Applicants often need programming, statistics, calculus, linear algebra, data structures, algorithms, or bridge coursework.

Do online AI master’s programs require the GRE?

Some require the GRE, some waive it, and others do not use it. Always verify the current GRE policy on the official admissions page.

What is the difference between AI and machine learning?

Artificial intelligence is the broader field of building systems that perform tasks associated with intelligence. Machine learning is a subset of AI focused on systems that learn patterns from data.

What programming languages are used in AI master’s programs?

Python is the most common language. Some programs may also use Java, C++, R, SQL, Julia, or cloud-based tools depending on the curriculum.

Do AI master’s programs cover generative AI?

Some newer or updated programs cover generative AI, LLMs, RAG, prompt engineering, AI agents, and responsible use. Students should verify course descriptions because coverage varies widely.

What should I look for in an online AI master’s program?

Look for institutional accreditation, transparent tuition, strong AI/ML curriculum, generative AI coverage, MLOps, responsible AI, applied projects, clear prerequisites, flexible delivery, and career support.

Are online AI degrees respected by employers?

Online AI degrees from accredited institutions can be respected, especially when the program is rigorous and the graduate can demonstrate strong projects, technical interviews, and relevant experience.

What portfolio projects should AI master’s students build?

Strong projects include deployed ML models, RAG chatbots, NLP tools, computer vision systems, model evaluation dashboards, responsible AI audits, MLOps pipelines, and domain-specific AI applications.

Online Master’s in AI Program Listings

Colorado State University Global
Aurora, Colorado
ARTiBA accreditation: No
Delivery method: Online
Total tuition: $24,300
2026 Cost per credit: $675
Credits: 36
GRE requirement: Not required
Learn more: Program details
DePaul University
Chicago, Illinois
ARTiBA accreditation: No
Delivery method: Online & campus
Total tuition: $86,800
2026 Cost per credit: $1,808
Credits: 48
GRE requirement: Not required
Learn more: Program details
Drexel University
Philadelphia, Pennsylvania
ARTiBA accreditation: No
Delivery method: Online & campus
Total tuition: $66,645
2026 Cost per credit: $1,481
Credits: 45
GRE requirement: Recommended for international students and for domestic students with a GPA below 3.0
Learn more: Program details
Duke University
Durham, North Carolina
ARTiBA accreditation: Yes
Delivery method: Online & campus
Total tuition: $99,000
2026 Cost per credit: $3,299
Credits: 30
GRE requirement: Not required
Learn more: Program details
Illinois Institute of Technology
Chicago, Illinois
ARTiBA accreditation: No
Delivery method: Online & campus
Total tuition: $53,400
2026 Cost per credit: $1,780
Credits: 30
GRE requirement: Not required
Learn more: Program details
Johns Hopkins University
Baltimore, Maryland
ARTiBA accreditation: No
Delivery method: Online
Total tuition: $54,550
2026 Cost per credit: $1,818
Credits: 30
GRE requirement: Not required
Learn more: Program details
Maryville University
St. Louis, Missouri
ARTiBA accreditation: No
Delivery method: Online
Total tuition: $28,875
2026 Cost per credit: $875
Credits: 33
GRE requirement: Not required
Learn more: Program details
Pennsylvania State University
University Park, Pennsylvania
ARTiBA accreditation: No
Delivery method: Online
Total tuition: $35,574
2026 Cost per credit: $1,078
Credits: 33
GRE requirement: Not required
Learn more: Program details
Rochester Institute of Technology
Rochester, New York
ARTiBA accreditation: No
Delivery method: Online & campus
Total tuition: $42,090
2026 Cost per credit: $1,403
Credits: 30
GRE requirement: Required for individuals with degrees from international universities
Learn more: Program details
Stevens Institute of Technology
Hoboken, New Jersey
ARTiBA accreditation: No
Delivery method: Online & campus
Total tuition: $41,850
2026 Cost per credit: $1,395
Credits: 30
GRE requirement: Required
Learn more: Program details
University of San Diego
San Diego, California
ARTiBA accreditation: No
Delivery method: Online
Total tuition: $28,950
2026 Cost per credit: $965
Credits: 30
GRE requirement: Not required
Learn more: Program details
University of Texas at Austin
Austin, Texas
ARTiBA accreditation: No
Delivery method: Online
Total tuition: $10,000
2026 Cost per credit: $333
Credits: 30
GRE requirement: Required
Learn more: Program details
University of the Cumberlands
Williamsburg, Kentucky
ARTiBA accreditation: No
Delivery method: Hybrid
Total tuition: $11,005
2026 Cost per credit: $355
Credits: 31
GRE requirement: Not required
Learn more: Program details
University of Bridgeport
Bridgeport, Connecticut
ARTiBA accreditation: No
Delivery method: Online & campus
Total tuition: $36,550
2026 Cost per credit: $1,075
Credits: 34
GRE requirement: Not required
Learn more: Program details
University of North Texas
Denton, Texas
ARTiBA accreditation: No
Delivery method: Online & campus
Total tuition: $29,224.14 in-state | $42,599.04
2026 Cost per credit: $885.88 in-state | $1,290.88 out-of-state
Credits: 33
GRE requirement: Required
Learn more: Program details