GetEducated has ranked 57 online master’s in AI and machine learning from 47 accredited schools based on total cost. These include specialized ML degrees as well as related programs in computer science, engineering, cybersecurity, business, and healthcare—so you can find a cost-effective option that fits your career goals.
ARTICLE NAVIGATION: Rankings Table | Career Guide
Average Cost (In-state): ~$33,000
Least Expensive (All Students): Georgia Institute of Technology ~$8,510
The 31 Cheapest Online AI and Machine Learning Master Degrees Programs
These rankings are based on GetEducated’s standardized evaluation framework for online degree programs. We assess accredited institutions using transparent cost calculations, published tuition data, and clearly defined inclusion and exclusion criteria. To ensure consistency across all of our rankings, we apply the same core methodology to each degree category.
Learn more about how we evaluate and rank online programs in our GetEducated Degree Ranking Methodology.
| Rank | School / Degree | State | Price | Note |
|---|---|---|---|---|
1 | Georgia Institute of Technology | (GA) | $8,510.00 | All Students |
2 | The University of Texas at Austin | (TX) | $10,000.00 | All Students |
3 | University of the Cumberlands | (KY) | $11,005.00 $9,765.00 | In-State/Out-of-State Military |
4 | Florida Gulf Coast University | (FL) | $11,201.00 $39,020.00 | In-State Out-of-State |
5 | Columbus State University | (GA) | $11,690.00 $8,104.00 | In-State/Out-of-State Military |
6 | Kennesaw State University | (GA) | $13,150.00 | All Students |
7 | Dakota State University | (SD) | $14,523.00 $17,993.00 | In-State Out-of-State |
8 | University of Central Missouri | (MO) | $14,897.00 | All Students |
9 | Troy University | (AL) | $15,675.00 $8,250.00 | In-State/Out-of-State Military |
10 |  Concordia University, St. Paul | (MN) | $15,750.00 $10,500.00 | In-State/Out-of-State Military |
11 | Indiana Wesleyan University | (IN) | $17,700.00 | All Students |
12 | University of South Florida | (FL) | $19,500.00 | All Students |
13 | Colorado State University Global | (CO) | $20,250.00 $13,500.00 | In-State/Out-of-State Military |
14 | Capitol Technology University | (MD) | $20,850.00 $11,850.00 | In-State/Out-of-State Military |
15 | Eastern Kentucky University | (KY) | $21,080.00 | All Students |
16 | New England College | (NH) | $22,095.00 | All Students |
17 |  Campbellsville University | (KY) | $22,908.00 | All Students |
18 | West Virginia University | (WV) | $23,550.00 | All Students |
19 | Saint Leo University | (FL) | $24,145.00 | All Students |
20 | University of Louisville | (KY) | $25,900.00 $7,900.00 | In-State/Out-of-State Military |
21 | University of Alabama at Birmingham | (AL) | $27,169.00 | All Students |
22 | Purdue University | (IN) | $28,000.00 | All Students |
23 | Auburn University | (AL) | $28,510.00 | All Students |
24 | University of San Diego | (CA) | $28,950.00 | All Students |
25 | Walsh College | (MI) | $29,310.00 | All Students |
26 |  George Mason University | (VA) | $29,550.00 | All Students |
27 | City University of Seattle | (WA) | $29,640.00 $12,168.00 | In-State/Out-of-State Military |
28 | Webster University | (MO) | $30,505.00 $15,490.00 | In-State/Out-of-State Military |
29 | West Virginia University | (WV) | $31,290.00 | All Students |
30 | Maryville University | (MO) | $31,975.00 | All Students |
31 | Nova Southeastern University | (FL) | $32,390.00 | All Students |
| School / Degree | State | Price | Note | |
|---|---|---|---|---|
University of Illinois at Chicago | (IL) | $33,012.00 | All Students | |
Pennsylvania State University | (PA) | $35,574.00 | All Students | |
University of Michigan - Dearborn | (MI) | $35,600.00 $44,300.00 | In-State Out-of-State | |
Robert Morris University | (PA) | $35,850.00 | All Students | |
University of Pennsylvania | (PA) | $38,370.00 | All Students | |
 Wake Forest University | (NC) | $38,940.00 | All Students | |
University of Denver | (CO) | $41,424.00 | All Students | |
Southern Methodist University | (TX) | $43,500.00 $23,250.00 | In-State/Out-of-State Military | |
Rochester Institute of Technology | (NY) | $43,980.00 | All Students | |
 Georgetown University | (DC) | $50,550.00 | All Students | |
Seattle University | (WA) | $53,573.00 | All Students | |
Illinois Institute of Technology | (IL) | $57,530.00 | All Students | |
Stevens Institute of Technology | (NJ) | $62,050.00 | All Students | |
Drexel University | (PA) | $66,895.00 $50,234.00 | In-State/Out-of-State Military | |
Stanford University | (CA) | $71,515.00 | All Students | |
Columbia University in the City of New York | (NY) | $81,575.00 | All Students |
Methodology for Rankings of the Most Affordable Online Master’s in AI and Machine Learning
These rankings of online artificial intelligence master’s programs are based on our fall 2025 review of degrees. In order to calculate the total cost, we use a variety of factors, including minimum required credit hours, tuition rates, and general fees. At the time of collection, the information was valid and specific to the individual program. Profiles for the same degrees found in the directory on our site may, on occasion, reflect a different cost based on editorial update schedules.
The published cost is an estimated total price for the entire degree, but actual costs will vary by student. For example, if you have transfer credits, your cost may be lower. Prerequisite courses, textbook fees, licensing requirements, financial aid, and numerous other factors can impact the price of an online master’s in AI or machine learning degree.
We strive to create the most honest, accurate ranking system possible. Therefore, we do not accept payments from schools to be included or removed from our rankings. The rankings are open to any regionally-accredited public or nonprofit college or university that offers an online AI or machine learning degree. We do not include degrees from non-accredited, nationally-accredited, or for-profit schools in our rankings. We also exclude from our rankings online master’s degree programs that are available less than 80% online and those that are only available to students in five states or fewer.
Program Note: In order to qualify for a ranking, the online machine learning or AI program must be regionally accredited. Additional programmatic accreditation is noted in the rank table. Online master’s degrees labeled with superscript 14 indicate that options for this program have changed since publication.
Difference Between an Online Master’s in AI and Machine Learning
Artificial intelligence (AI) is a fast-moving field, and many people are just beginning to explore what it is and how it works. At its core, AI is all about building systems that can mimic human intelligence to handle tasks like reasoning and problem-solving in a fraction of the time.
One key area within AI is machine learning, a specialized branch that uses learning algorithms and machine learning algorithms to analyze input data, recognize patterns, and improve system performance over time, all without being explicitly programmed. Machine learning is a set of techniques within data science that automates data analysis and applies insights to real-world tasks.
Machine learning can be categorized into three main paradigms: supervised learning, unsupervised learning, and reinforcement learning. Supervised learning algorithms require labeled input data, known as training data, and are used for tasks such as classification and regression. Each training example in supervised learning consists of input data paired with the desired output, allowing the model to learn to make accurate predictions on new, unseen data. Unsupervised learning algorithms identify patterns in data without labeled outputs and are often used for clustering and dimensionality reduction. These algorithms focus on intrinsic data properties rather than predefined outcomes and are also used for anomaly detection. Reinforcement learning is a type of machine learning where agents learn to make decisions by receiving rewards or penalties based on their actions, training models through trial and error to maximize cumulative reward.
Traditional machine learning relies on explicit algorithms and manual feature engineering, serving as a foundational approach in AI development. In contrast, deep learning—a subset of machine learning—uses large artificial neural networks with many layers to model complex patterns in data. Deep learning models are built using artificial neural networks, which are inspired by the structure and function of the human brain. These networks emulate neural processes such as learning and signal transmission, drawing parallels between artificial neurons and actual neurons in the brain. Activation functions play a crucial role in neural networks by enabling nonlinear transformations at each neuron, allowing the modeling of complex patterns and dependencies. Deep learning algorithms have emerged as the state-of-the-art AI model architecture, capable of hierarchical feature extraction and surpassing traditional machine learning in tasks like image and speech recognition.
The central premise of machine learning is that if you optimize a model’s performance on a dataset of tasks that resemble real-world problems, the model can make accurate predictions on new data. Machine learning and statistics are closely related fields: statistics draws population inferences from a sample, while machine learning finds generalizable predictive patterns.
AI systems encompass a broad range of approaches, from rule-based systems to advanced machine learning and deep learning models.
While machine learning degrees often dive deep into advanced computer science topics like algorithm design, data modeling, and statistical analysis, degrees in artificial intelligence offer a broader, more versatile foundation. AI programs prepare professionals across a range of industries to use intelligent systems that streamline processes. This reduces manual work and boosts productivity.
The term ‘machine learning’ was coined in 1959 by Arthur Samuel, an IBM employee and pioneer in artificial intelligence.
Top Reasons to Earn an Online Master’s in AI or Machine Learning
The rise of artificial intelligence will inevitably lead to the transformation and loss of certain jobs, but it’s also creating new opportunities. According to the Bureau of Labor Statistics, AI and machine learning are expected to boost employment in computer and technology fields, while also giving rise to new roles across most industries. For example:
- Personal finance firms are using AI to deliver automated investment advice.
- Legal professionals are leveraging AI to reduce research time and improve efficiency.
- Manufacturing and engineering are using machine learning to drive productivity gains.
- Healthcare AI careers are poised to benefit research even more in the years ahead.
Earning an online degree in AI or machine learning positions you to become a valuable asset in this shifting landscape, in public, private, and non-profit sectors, from small to large. With the right skills, you can expand your career prospects and help organizations navigate and compete in the AI-powered future.
Why invest thousands in a fast-moving field like AI? Will today’s skills still matter tomorrow? Absolutely, and here’s why:
- In-Demand Skills, Future-Proof Knowledge
You’ll build a strong foundation in AI while learning how to apply it in real-world settings. These aren’t just trendy buzzwords; they’re critical tools that top tech companies are looking for right now. By understanding AI early, you’ll have a competitive edge that opens doors to exciting roles.
- Higher Pay, Faster ROI
A master’s degree doesn’t just increase your knowledge, it boosts your paycheck too. Graduates often start in leadership roles with higher salaries, meaning your return on investment begins on day one. The degree pays for itself faster than you might think.
- More Career Options, More Flexibility
Want to start your own business? Move up in your current company? Change industries completely? A master’s degree can help you get there. Many programs offer electives, allowing you to tailor your path, and they also provide access to global professional networks. You’ll meet experts, collaborators, and mentors, all of which can lead to career moves you didn’t even see coming.
What to Look for in an Online Master’s in Artificial Intelligence Program
Factor all information to narrow your choices and find a program that works for you.
Cost is top of mind. Use the table to quickly search for the total estimated cost, based on your residency or potential military eligibility.
Goals. What do you plan to do with your degree? Review degrees’ overviews and what they have to offer to ensure that the knowledge and skills gained will allow you to reach your potential. Don’t fit yourself into a degree. With many options out there, find an online master’s degree tailored to your goals.
Reputation is equally important. Rest assured, this dataset only lists regionally-accredited schools. Regional accreditation demands the highest standards in education. Schools must have a public or not-for-profit operational status. For-profits are not considered.
Lifestyle. A college degree is a major investment, one that’s too valuable to leave unfinished. That’s why it’s important to find a program that fits your schedule and lifestyle. The programs on our list are 100% or mostly online. You may need to pack a suitcase for a brief weekend session, but you won’t need to pack up and move.
How Much Does an Online Master’s in Artificial Intelligence Cost?
An online master’s degree is a smart investment in your future. Even higher-priced programs can offer strong long-term value, helping graduates boost their income and advance in their careers. But choosing the right degree takes careful planning, especially when it comes to cost.
In this database, you’ll find 57 programs from 47 accredited, well-regarded institutions. Prices range from under $9,000 to over $80,000, a difference of about $71,000. With such a broad range, it’s important to choose a program that aligns with your financial goals.
The most affordable online master’s in artificial intelligence is offered by the Georgia Institute of Technology (Georgia Tech). Their Master of Science in Computer Science includes concentrations in Machine Learning and Interactive Intelligence, with a total estimated cost of $8,510. That rate applies to both in-state and out-of-state students, making it an excellent value no matter where you live.
The average cost of the programs in this database is $33,000. Most can be completed in just one to two years (3 to 4 semesters) and also offer flexible part-time options. However, master’s degrees can take between one and three years to complete depending on the program and structure. Most MA and MS degrees require 30 to 36 credits and typically take 1–2 years to complete.
At the other end of the spectrum, the most expensive program is Columbia University’s Master of Science in Computer Science with a Machine Learning Track, priced at $81,575. The second most costly is Stanford University’s Computer Science in Artificial Intelligence program, estimated at $71,515. Both schools are highly prestigious, with Columbia holding Ivy League accreditation.
While price isn’t the only factor to consider, it’s a big one for most students. Use this database and information about different online AI master degrees to compare programs and find the one that fits both your career goals and your budget.
A Closer Look at the Cheapest AI Master’s Degrees Online to Advance Your Career
These programs are a subset of the broader graduate school landscape, which includes options like medical schools and other professional programs. Graduate school offers a variety of pathways for career preparation, with program rankings, application strategies, and admissions guidance available for prospective students.
View details for some of the most affordable programs to help narrow choices and find a perfect degree to match your needs. These schools charge the same tuition, regardless of residency.
Georgia Institute of Technology (Georgia Tech)- Focus: Computer Science / Machine Learning or Interactive Intelligence
- Format: 100% online, complete two courses per semester
- Start dates: Fall or spring semester starts
- Estimated completion: 2-3 years
- Prerequisites: 3.0 GPA with a background in computer science or a related field preferred. Typically, most master’s programs require a bachelor’s degree for admission.
- Machine Learning Sample Curriculum: Intro to graduate algorithms, computational science, machine learning, and data analysis
- Interactive Intelligence Sample Curriculum: Software development, computational science, engineering algorithms, and machine learning
- What sets this degree apart: Partnerships with Udacity and AT&T keep tuition rates low.
- Focus: Artificial Intelligence
- Format: 100% online, asynchronous courses
- Start dates: Per semester
- Estimated completion: 1.5-3 years
- Prerequisites: 3.0 GPA with a background in a related field highly preferred. Typically, most master’s programs require a bachelor’s degree for admission.
- Sample curriculum: Deep learning, ethics in AI, machine learning, and reinforcement learning
- What sets this degree apart: The school does not cap admissions for this program.
- Focus: Artificial Intelligence
- Format: 100% online, 8-week term, 2 terms per semester. Most courses are asynchronous.
- Start dates: Per semester
- Estimated completion: 2 years
- Prerequisites: 2.5 GPA with a bachelor’s degree in a related field recommended. Typically, most master’s programs require a bachelor’s degree for admission.
- Sample Curriculum: AI, machine learning, data mining, and natural language processing. This program does not permit elective options.
- What sets this degree apart: Begin with a graduate certificate and apply those credits to the master’s program. Benefit from free textbook rentals. Reduced tuition is available for eligible service members and veterans.
Common types of master degrees include:
- Master of Arts (MA): Focuses on humanities and social sciences.
- Master of Fine Arts (MFA): A practical degree for visual arts and creative writing.
- Master of Science (MS): Emphasizes technical and scientific fields such as STEM and healthcare.
- Master of Business Administration (MBA): A professional degree focused on leadership and management.
Types of Online Master’s Degrees in Artificial Intelligence, Machine Learning, and Machine Learning Models
Here is a look at different types of online master’s degrees in AI or machine learning. Think about where you want your career to go, and you’ll be able to match the degree type and concentration that fits best. In addition to traditional supervised and unsupervised learning, semi-supervised learning is another important approach covered in these programs, leveraging both labeled and unlabeled data to improve model performance.
Degree curricula typically include instruction on the training model process, where students learn about data preparation, model optimization, and evaluation to ensure accuracy and fairness. Coursework also emphasizes the importance of representing data as numerical values, such as vectors and feature vectors, which is essential for feeding data into machine learning and AI algorithms.
Specialized AI and Deep Learning Careers
Master of Artificial Intelligence (MAI). If you want to work directly in AI-focused roles (like machine learning engineer, NLP specialist, or AI ethicist), this program sets you up with targeted knowledge and fewer distractions from unrelated coursework. Students may study advanced topics such as deep reinforcement learning, which combines deep neural networks with reinforcement learning to enable agents to learn complex behaviors. The curriculum also covers recurrent neural networks for their ability to process sequential data and understand context in tasks like language modeling. Graduates are trained to apply AI and machine learning models to specific tasks such as image classification, natural language processing, or predictive analytics, and these models are trained to perform tasks such as recognition, classification, and decision-making, often building classification models for targeted applications.
Flexible Career Options
Master of Science (MS or MSc). Perfect for students who want both breadth and depth. You’ll get a strong computer science foundation plus an AI concentration, which means you can pivot between research, technical roles, or even leadership in the future. Students also gain hands-on experience working with AI algorithms and AI systems to build, deploy, and scale machine learning models across different platforms, as well as developing AI models for a variety of research and technical applications.
Master of Engineering (MEng or ME). Best for students who want to get into the workforce quickly with hands-on skills. The capstone project and professional focus make you job-ready faster than most other degree types. Students often work with AI tools and machine learning systems to solve real-world engineering problems and gain practical, hands-on experience. MEng programs also teach students how to manage computational resources efficiently when training AI models for complex tasks in engineering and industry.
Master of Philosophy (MPhil). Ideal if you see yourself continuing into doctoral work. The thesis and oral defense help you build research and analytical skills that prepare you for a PhD or academic career. Students also gain expertise in advanced machine learning methods and the training process for developing and evaluating research models. Research projects may involve predicting continuous values using regression models.
Master of Research (MRes). Similar to the MPhil, but with more structured research training. This degree helps you develop the discipline and methodology needed for academic research or high-level R&D roles in industry. Students are exposed to a variety of machine learning methods and learn about the training process, including data preparation and model optimization, which are essential for conducting rigorous research. Students also learn to use historical data for time series analysis and forecasting.
Salary Expectations with an Online Master’s in Artificial Intelligence
Graduates can pursue careers that range from hands-on engineering roles to high-level research and business leadership. Salaries are among the highest in tech, with many positions starting well into six figures and rising significantly with experience, specialization, and bonuses.
Machine learning models are widely used in these high-paying roles, powering applications such as recommendation systems (like those used by Netflix) to predict user preferences, fraud detection in finance, and the development of autonomous vehicles. Natural language processing (NLP) enables tasks like language translation and sentiment analysis, while computer vision is used in applications such as image recognition and autonomous driving. Large language models and generative AI tools are pushing the boundaries of AI capability, including tasks like text generation and data compression. AI agents and generative AI applications are also becoming increasingly important in both business and research, enabling accurate predictions and driving innovative solutions across industries
What can you earn with an online AI master’s degree?
Career Path | Average Salary |
|---|---|
| Machine Learning Engineer | $140K |
| AI Engineer | $135K |
| Data Scientist | $125K |
| Computer Vision Engineer | $145K |
| NLP Engineer | $140K |
| AI Research Scientist | $150K+ |
| Research Engineer | $130K |
| AI Product Manager | $160K |
| AI Consultant | $140K |
| BI Analyst (AI-focused) | $110K |
| Robotics Engineer | $120K+ |
| AI Ethics Specialist | $125K |
| AI Solutions Architect | $150K |
Takeaway: Graduates with an online master’s in artificial intelligence typically earn between $130K and $200K+, depending on their career path. Builders such as engineers and data scientists average $125K to $150K, innovators in research often exceed $150K (with elite roles reaching $300K+), and business-focused professionals like AI product managers can see $160K to $200K+ with equity and bonuses.
Why Accreditation Matters for an Online Master’s in Artificial Intelligence
If you’re going to spend thousands of dollars on a degree, you need confidence that your investment is worthwhile. One of the best ways to ensure quality is to choose a program from an accredited school.
Accreditation works like higher education’s quality-control system. Independent organizations review colleges and universities to confirm they meet rigorous standards in areas like curriculum, faculty, and student outcomes. The most important type of accreditation is institutional accreditation, and within that, regional accreditation is the gold standard.
Regional accrediting bodies include:
- Higher Learning Commission (HLC)
- Middle States Commission on Higher Education (MSCHE)
- New England Commission of Higher Education (NECHE)
- Northwest Commission on Colleges and Universities (NWCCU)
- Southern Association of Colleges and Schools Commission on Colleges (SACSCOC)
- WASC Senior College and University Commission (WSCUC)
Every program in this database comes from a regionally accredited institution, giving you confidence that your degree will hold value, both academically and in the job market.
Prerequisites for Online AI Master’s Programs: What You Need to Apply
Most online AI master’s degrees expect applicants to come in with a solid technical foundation. While requirements vary by school, here are the typical prerequisites you’ll see:
Academic Background
An accredited bachelor’s degree in a related field: computer science, engineering, mathematics, statistics, or a closely related discipline.
Some computer science-related programs accept students from other fields if they’ve taken the right technical coursework. Others provide bridge courses to fulfill admission requirements.
Coursework & Skills
- Mathematics: Linear algebra, calculus, probability, and statistics are almost always required. Foundational courses often include topics such as linear regression, which teaches students how to model relationships between input variables and predict numerical values.
- Programming: Proficiency in at least one common language (often Python, Java, or C++).
- Computer Science fundamentals: Data structures, algorithms, and sometimes operating systems.
- Machine Learning / AI basics: Not always mandatory, but having prior exposure gives you a strong advantage. Exposure to data science and machine learning techniques is highly beneficial for applicants. Understanding how to represent data points as numerical values is essential for machine learning coursework. During data preparation and model training, it is also crucial to address data bias to ensure fairness and accuracy in machine learning models.
Professional or Academic Extras
- GPA requirements: Usually a minimum of 3.0 on a 4.0 scale.
- GRE scores: Some schools still ask for them, though many are test-optional now.
- Letters of recommendation: From professors or employers who can vouch for your technical ability.
- Statement of purpose: Explaining your goals and why you want to specialize in AI.
While AI was once considered the realm of science fiction, it now powers real-world applications such as self-driving cars, demonstrating its transformative impact across industries.
In short: if you have strong math, coding, and computer science foundations, you’ll meet the prerequisites for most MSAI programs.