Top 25 Online Master’s In AI Programs for 2027

Program Summary

• MS in Artificial Intelligence
• Estimated tuition: $10,000 
• Typical length: 1.5-2 years
• Accreditation: SACSCOC
• Credits: 30 
• Best for: Academic quality, affordability

About the program

The University of Texas at Austin stands out for its extremely affordable price point. $10,000 is a fraction of the typical cost for a flagship university at this level. But the highly customizable program structure is just as notable: AI ethics is the only core unit, and the remainder of the program is made up of 9 electives.

This program wins the top slot because it offers the best overall value in our 2026 rankings. It combines its unusually low total tuition with an elite computer science reputation: UT Austin is an R1 institution with a top-10 CS department, so graduating from this program will make you a prime candidate for future employers. 

Traditional R1 programs can cost upwards of $50,000, so the remarkable $10,000 cost offers a tremendous potential return on investment (ROI). The online program is also asynchronous, allowing you to complete your degree alongside existing career commitments.

Curriculum highlights

If you have a particular specialization in mind, the University of Texas at Austin is a brilliant choice for you. That’s down to the massive freedom over electives. 

There are 4 “foundational” courses, which students are advised to complete before embarking on their electives:

• Deep Learning
• Machine Learning
• Planning, Search, and Reasoning Under Uncertainty
• Reinforcement Learning

But Ethics in AI is the only course that is strictly required, underscoring UT Austin’s commitment to this important topic. Here are some examples of the weekly topics from that course:

• Week 1: Indian Ethics/Classical Chinese Ethics/Babbage’s Engines
• Week 4: Kantian Ethics/Consequentialism/Deep Blue
• Week 6: Ethics of Care/Ubuntu/Autonomous Cars
• Week 11: Accountability

This looks like a truly fascinating, multi-disciplinary course. And once you’ve completed it, you can embark on a whole range of similarly interesting electives that will allow you to begin moving into your preferred field of study.

Electives include AI in Healthcare, Online Learning and Optimization, and Advances in Deep Generative Models. The course design places a strong emphasis on hands-on work rather than lectures, allowing you to implement and evaluate AI systems firsthand.

Program Summary

• MS in Artificial Intelligence
• Estimated tuition: $27,990
• Typical length: 2 years
• Accreditation: HLC
• Credits: 30
• Best for: Academic quality

About the program

Purdue’s MS in Artificial Intelligence program comes with a choice of 2 majors: AI and Machine Learning, and AI Management and Policy. The choice of a technical or management focus means you’ll be able to get a degree that closely aligns with your career goals. 

Tuition comes in at just $28,500. Although that’s significantly more than UT Austin, it’s still cheaper than average, and you’re paying for significant institutional prestige (Purdue is a top-20 public school nationwide).

In terms of prerequisites, the AI/ML path requires prior programming experience and coursework (in Python, Data Science, and/or Computer Science) and prior coursework in algorithms, linear algebra, and probability theory. The AI management track requires at least 24 months of work experience.

Curriculum highlights

Both majors in the program comprise 30 credit hours. In either track, you’ll be required to take 4 core courses: 

• AI fundamentals
• AI policy and ethics
• Societal impacts of AI
• A three‑credit capstone

Depending on the major you’ve chosen, you’ll then branch out into either AI/ML and Data Mining or Applications of AI in Business. 

If you want to take any of the courses from the other major, you can choose them as electives. Otherwise, you’ll pick 3 alternative Technical/Professional electives and 1 graduate-level course from any area of study (with approval from an advisor).         

Program Summary

• MS in Artificial Intelligence
• Estimated tuition: $15,750
• Typical length: 1-2 years
• Accreditation: HLC
• Credits: 30
• Best for: Admissions

About the program

The University of Colorado Boulder’s online MS in AI is notable for its innovative admissions process. You don’t technically have to “apply” at all: you can automatically enroll into 3 different 1-credit pathway courses in statistics and computer science. If you complete your pathway with a GPA of 3.0 or higher, with at least a B grade in each course, you’ll be admitted. Better yet, the credits will count toward your final master’s degree.

As such, this program is best for anybody anticipating hurdles in their admissions process, whether it’s transcripts or letters of recommendation. If you want to pursue a real AI master’s degree from a research-driven university, CU Boulder makes it accessible. This makes it an especially solid offer for career switchers (who might not have the extensive background required for a traditional university admissions process) and motivated international students.

Boulder’s program is also the only one on our list delivered through Coursera. But it’s not a typical “Coursera certificate”: it’s a standard CU Boulder graduate program that just happens to make use of a purpose-built online learning platform. You’ll get on-demand access to all of the course content, so you can complete the program at your own pace, finishing in as little as 12 months. And your final diploma won’t mention Coursera or distinguish between campus and online study. If you want to “try before you buy”, you can instantly enroll in the non-credit experience to preview course content.

Curriculum highlights

The 30 credit hours are broken down into 15 breadth courses (including the admission pathway courses) and 15 electives. Each course is worth 1 credit, but courses are clustered into groups of 3 (“specializations”). When it comes to electives, you must complete at least 4 full specializations, but you can mix and match for the final 3 credits.

One example of a specialization is Data Mining Foundations and Practice. That’s broken down into the following 3 courses:

• Data Mining Pipeline (1 credit)
• Data Mining Methods (1 credit)
• Data Mining Project (1 credit)

More than 10 specializations are “currently in development”: a good sign that the curriculum is being kept up to date, although it does make your choices slightly narrower in the meantime. Current options include Foundations of Autonomous Systems, Introduction to Robotics (with Webots Specialization), and Introduction to Computer Vision. Most courses contain an element of project-based work to reinforce practical skills. 

Program Summary

• Master of Artificial Intelligence
• Estimated tuition: $35,574
• Typical length: 1-4 years
• Accreditation: MSCHE
• Credits: 33
• Best for: Stackable credentials

About the program

Penn State is a top-30 public university that is highly respected by employers. Its World Campus is a well-established online delivery method, so everything is set up for distance learning. You’ll be able to take things at whatever pace works for you, and a helpful guide to timelines is supplied:

• To finish in 1-2 years: 3-4 courses per semester
• To finish in 2-3 years: 2-3 courses per semester
• To finish in 3-4 years: 1 course per semester

When you graduate, you’ll get the same diploma you would earn from studying on campus.

At a little over $35,000, the Master of Artificial Intelligence program is a significant investment. But as well as the institutional prestige, you’ll benefit from Penn State’s membership of the Linux Foundation. This will offer opportunities to contribute to real-world AI projects. You’ll have the chance to gain further hands-on practice through AI/ML events and competitions.

Curriculum highlights

You can choose to complete the Master of Artificial Intelligence program at Penn State as a series of graduate certificates. You simply need to apply, gain acceptance, and then complete the requirements of each certificate track below:

• Foundations of Artificial Intelligence (12 credits)
• Natural Language Processing (9 credits)
• Computer Vision (9 credits)

Each of these qualifications is standalone, so you can start adding them to your resume as you complete them. That could give you a notable headstart in the job market, particularly useful if you think the full degree will take you a long time to complete. Once you’ve earned all of the certificates, the only thing you’ll need to do to finish your master’s in AI is a 3-credit capstone course.

The Penn State MAI program is focused on data, research, and algorithms. You’ll do 21 credits of core courses, and 9 credits of electives, with options including Reinforcement Learning, Data Visualization, and Foundations of Predictive Analysis.

Program Summary

• Online MSE in Artificial Intelligence
• Estimated tuition: $40,270
• Typical length: 16-40 months
• Accreditation: MSCHE
• Credits: 10 units (~30 credits)
• Best for: Affordable Ivy League option

About the program

The only Ivy League option on our list, The University of Pennsylvania’s online MSE in Artificial Intelligence is brilliant for your resume. The trade-off is more stringent admissions requirements than many of the alternatives: you’ll need an undergraduate degree in computer science or a related field, 2-3 letters of recommendation, and a resume and personal statement that showcase some level of professional experience. GRE scores are optional, but can improve your chances of success.

But if you’ve got the right background to gain admission, Penn’s program is superb, offering real value for money. The faculty are genuine industry leaders: the program director has received faculty research awards from Google, Microsoft, Amazon, and Facebook, and has previously testified about generative AI before Congress.

You’ll be able to complete the program in as little as 16 months (3 units for the first 2 semesters, 4 units in the final semester). But you pay per credit, so there’s no financial penalty for taking the minimum course load, spreading the program out over 40 months.

Curriculum highlights

One of the reasons this program stands out is that it leans heavily into advanced applied theory and mathematically grounded AI methods. Across 10 units, you’ll be getting an education in areas such as machine learning, deep learning, probabilistic modeling, optimization, and domain‑specific AI applications.

As an example, let’s look at Statistics for Data Science, 1 of 6 core units. You’ll cover:

• Linear and nonlinear regression
• Classification
• Uncertainty quantification
• Model validation
• Clustering
• Dimensionality reduction
• PAC learning

And you won’t just be taught the theory. You’ll study example applications and case studies, and complete relevant programming exercises in Python.

This level of granularity is great for students who want to target moves into senior practitioner roles, research‑adjacent positions, or eventual PhD study.

Program Summary

• MS in Artificial Intelligence in Medicine
• Estimated tuition: $25,500
• Typical length: 2 years
• Accreditation: SACSCOC
• Credits: 30
• Best for: Medical AI practitioners

About the program

The University of Louisville’s MS in Artificial Intelligence in Medicine is a specialized AI degree for medical professionals. It focuses on the intersection of AI and medicine, covering topics like medical imaging and medical data analysis. Potential graduate careers include Director of Medical Imaging, Healthcare Data Analyst, and Computational Biologist. 

It is one of the few specialized AI healthcare degrees out there. There are other programs that offer medical AI concentrations (e.g. the Biomedical Engineering master’s at Johns Hopkins), but a fully dedicated program is rare. And it’s competitively priced, with total tuition of just over $25,000. Active-duty members of the military pay just $7,500.

Average completion time is 2 years. You can technically finish in a year if you take 4 courses in the fall and the spring, and a further 2 in the summer, but the university recommends 1-2 courses per semester.

Curriculum highlights

Most of the Louisville program (24/30 credits) is made up of core topics. These include Machine Learning in Medicine, Medical Image Computing, and Introduction to AI in Bioengineering. You’ll also do a non-thesis design/research project under the guidance of a faculty member, which could be a useful portfolio piece.

You will get to choose 2 electives, which will allow you to start specializing in specific fields of AI medicine. Options include AI Techniques in Digital Pathology, AI and Radiomics, and Computational Methods for Medical Image Analysis.

Program Summary

• MS in Artificial Intelligence
• Estimated tuition: $15,750
• Typical length: 1.5 years
• Accreditation: HLC
• Credits: 30
• Best for: Affordability and accessibility

About the program

Concordia University, St. Paul offers an online MS in Artificial Intelligence through CSP Global. It stands out immediately for its price, which is among the lowest on our list. But the cost is only half the story, and CSP is also a great pick for you if you’ve got practical concerns about the admissions process. It is highly streamlined:

• No GRE/GMAT required
• Six different start dates throughout the year
• Transfer in up to 15 graduate credits from an accredited university
• No application fee

You do still need a bachelor’s degree with a minimum GPA of 3.0, but there is no need for it to be in computer science or a similarly technical subject. The program is designed for professionals of all backgrounds, and foundational competencies are taught alongside advanced topics. 

Curriculum highlights

CSP Global stands out for what it calls “experiential learning”. This is at the heart of the Master’s in AI curriculum. Essentially, coursework is built around real-life scenarios as opposed to abstract problem sets. You’ll focus on addressing realistic business and technical situations using cloud-based environments and AI solutions. 

It’s important to be aware that all 10 courses are considered core, so you won’t get any choice of electives. But while the curriculum may be somewhat prescriptive, it does provide strong coverage of the main areas you’d expect to see, including deep learning and neural networks, training ML and LLM models, reinforcement learning, and computer vision. You’ll also cover leadership, ethics, and bias in AI.

Program Summary

• Online MS in Artificial Intelligence
• Estimated tuition: $39,062 ($21,510 for Texas residents)
• Typical length: 1.5-2.5 years
• Accreditation: SACSCOC
• Credits: 30
• Best for: Academic quality

About the program

Texas A&M’s online MS in Artificial Intelligence is offered by the Department of Computer Science and Engineering. It’s a designated STEM program, and you should expect a fairly math-heavy focus: algorithms and statistics courses are both prerequisites. But while it may be academically challenging, you will be rewarded with a very well-respected degree: TAMU is an R1 school.

This is one of the few programs that still charges different resident and non-resident rates, even for its fully-online program. The cost rises steeply if you’re outside of Texas. And regardless of residency, you should be prepared for the high “remote program fees” (outside of the main tuition rate), which can rise up to $5,000 per semester depending on your course load. But this is all transparently reflected in their tuition calculator.

Curriculum highlights

Texas A&M technically only has 2 required courses: Artificial Intelligence and Machine Learning. But a further 5 are called “prescribed electives”, where you’ll have to pick 5 from a choice of 6. That guarantees coverage in a number of important areas including reinforcement learning, intelligent agents, and natural language processing.

Your final 3 courses will be true “free electives”, where you’ll get the chance to branch out into related areas of computer science and engineering. A thesis option is available, but not required.

Program Summary

• MS in Applied Artificial Intelligence
• Estimated tuition: $29,850
• Typical length: 20 months
• Accreditation: WSCUC
• Credits: 30
• Best for: Graduate outcomes

About the program

The University of San Diego offers an “applied” AI master’s, and the program lives up to that name. It’s a really impressive curriculum, built in collaboration with industry and government partners and designed to genuinely prepare you for a career in AI.

USD’s AI program has been up and running long enough to see some genuine graduate outcomes (it launched in 2020). And the results are impressive: the average reported salary is $116,510, and employers include Amazon, Nvidia, Apple, and Google.

The online program is part-time, but you’ll still finish in 20 months (vs 16 months on-campus), working through 2 courses per semester. There are Fall, Spring, and Summer intakes, so you never have to wait too long to get started. Once you’re enrolled, course content is primarily asynchronous, but you will benefit from live Q&As and office hours. 

Curriculum highlights

The capstone project really sums up all of the best things about San Diego’s MSAAI. You’ll be building an AI system from scratch, designing it to tackle a real-world problem. Previous examples include an AI stock trading system, a virtual teaching assistant, a fake news detector, and a lung disease detection model.

Before you get to that stage, you’ll take 9 other courses, each designed to give you a real grounding in applied AI. You’ll cover neural networks, GenAI, applied computer vision, AI ethics and more. Unlike some other programs, you won’t get a choice of electives, but the prescribed degree plan is well-designed to set you up for workplace success.

Program Summary

• MS in Artificial Intelligence
• Estimated tuition: $56,200
• Typical length: 1.5-3 years
• Accreditation: MSCHE
• Credits: 30 
• Best for: Academic quality, degree customization

About the program

Johns Hopkins boasts serious academic credentials, and the MS in AI is no exception. You will benefit from teaching delivered by genuine leaders in the field: the program chair has a background in JHU’s own Applied Physics Laboratory, while the program manager is a former US Army Officer with a PhD in Computational Analysis and numerous published papers to his name.

You need to be prepared for a high academic standard. To that end, you are required to have completed certain prerequisites in topics such as calculus, linear algebra, and programming, although you can sit a proficiency exam instead if you have extensive experience but lack formal qualifications. You’ll also need a GPA of at least 3.0 from your bachelor’s degree.

Once enrolled, you’ll pay an undeniably premium price tag. But as this qualifies as an Engineering for Professionals program, the Dean’s Fellowship is automatically applied, so the listed tuition fee is cheaper than some other Johns Hopkins master’s programs. And it’s no secret what you are paying for: world-class teaching and almost unmatched institutional prestige. Moreover, 78% of students have their tuition covered by employer contribution programs, an incredible option if it is available to you.

Curriculum highlights

A secondary benefit of JHU’s industry-leading AI expertise is a massively customizable curriculum. Coverage is so extensive that you’re able to select from 5 different tracks: Assured Autonomy, Decision and Leadership, Deep Learning, LLMs, and Robotics. These aren’t formal designations (and won’t show up on your diploma), but they’re useful for plotting a degree route among the 40+ electives on offer.

You’ll choose a total of 6 electives from the vast selection. These are just a handful of examples:

• Production AI
• Responsible AI
• Neuromarketing AI
• Cognitive and Behavioral Foundations for AI
• ChatGPT from Scratch
• Advanced Artificial Intelligence
• Deep Learning for Computer Vision
• Generative AI and Synthetic Threats

The remainder of the program is made up of core units. These are as follows:

• Introduction to Generative AI/Applied Generative AI
• Creating AI-Enabled Systems
• AI Algorithm Design and Analysis
• Applied Machine Learning

Program Summary

• Online Master of Science in Artificial Intelligence
• Estimated tuition: $25,245
• Typical length: 2 years
• Accreditation: HLC
• Credits: 33
• Best for: Admissions, hands-on practice

About the program

Maryville University stands out for its hands-on, project‑based coursework. Each course involves a practical element, and the program culminates in a capstone project where you’ll work as part of a team to solve a real-world problem. You’ll also be learning on industry-standard tools like AWS and Google Colab, so your graduate-level knowledge should carry over seamlessly into the workplace. 

The program also stands out for its admissions process. You won’t require GRE or GMAT, and there’s a “transfer credit friendly” policy: up to 6 external graduate credits, or 12 previously completed at Maryville. There are also 3 separate start dates throughout the year. 

Curriculum highlights

You can choose to make the Maryville program even more hands-on by opting for an internship as up to 2 of your 3 electives. In theory, you can spend up to 300 hours in industry, earning 6 credit hours in the process.

Meanwhile, the majority of the curriculum is made up of 24 credits of required AI core courses. These lay the foundation in Python programming, the mathematics of AI, machine learning, deep learning, and AI ethics, culminating in a capstone project that integrates these skills in an applied setting.

The MS program at Maryville also technically works on a stackable credentials model. So by the time you graduate, you’ll also have 2 graduate certificates:

• Fundamentals of Artificial Intelligence
• Advanced Artificial Intelligence

Program Summary

• MEng in Artificial Intelligence and Machine Learning
• Estimated tuition: $32,256
• Typical length: 1-2 years
• Accreditation: HLC
• Credits: 36
• Best for: Engineering focus

About the program

Unlike most programs on our list, the University of Illinois Chicago program isn’t strictly a master’s in AI. You’ll actually be earning an “MEng” (Master of Engineering), and AI and Machine Learning is listed as a concentration.

This route won’t be suitable for everyone. As an engineering program first and foremost, it has a math-heavy curriculum. And UIC is an R1 institution that expects a strong academic background: a GPA of at least 3.0 in undergraduate study, either in engineering or a closely related field. If you aren’t a STEM major you can technically still qualify with Calculus 1-3 and 10+ credit hours in sciences, but realistically this probably isn’t the right program for you if you first need to complete all of these prerequisites.

However, if you do come from an engineering background, this is a great way of getting a rigorous AI education that will be deeply respected by employers. The MEng label will open up a number of potential career avenues including Machine Learning Engineer, Computer Vision Engineer, and Natural Language Processing Engineer, all of which require highly technical backgrounds and skills. There’s also a clearly-defined pathway to earning the degree in 1 year. 

Curriculum highlights

This is a hands-on engineering program. As such, there’s no thesis option, so you’ll probably want to look elsewhere if you’re targeting a career in academia.

Unusually, each course is worth 4 credit hours, and you’ll take 9 courses altogether (for a total of 36 credit hours). It’s a wholly prescriptive curriculum, so you won’t get any electives. But you will cover all of the main technical ground, e.g. neural networks, deep learning, and natural language processing. 

Perhaps surprisingly for an MEng, 3 of the 9 courses are dedicated to AI leadership skills, with the goal of helping you apply your technical knowledge to real workplaces. Courses on engineering law, innovation tools and methods, and management help position graduates as engineers capable of leading AI‑driven initiatives.

Program Summary

• MS in Computer Science, AI and ML Specialization
• Estimated tuition: $8,770-$17,540
• Typical length: 19 months
• Accreditation: NWCCU
• Credits: 10 courses (equivalent to ~30 credits)
• Best for: Affordability, embedded certifications

About the program

Western Governors has the potential to be a brilliant option for you, as long as you know exactly what you’re signing up for. It’s probably the most unique program on our list.

Crucially, WGU is built around self-directed study. You’ll be provided with all of the learning materials, and left to work through them independently. There is faculty on hand if needed, and you’ll be assigned a program mentor, but this is not the program for you if you want to be truly guided through the content.

However, if you’re already technically strong on AI and just looking to certify that expertise, or if you’re an extremely self-disciplined student, the WGU approach comes with massive benefits. You’re charged per term, so if you work through the material quickly, you could pay as little as $8,770 (2 x 6-month terms). You can access the content and even sit your exams whenever you feel ready. And the low-cost includes industry-standard external qualifications, most notably AWS Certified Machine Learning Engineer – Associate. Two-thirds of WGU graduates finish similar programs within 19 months. And graduates of the School of Technology see an average salary increase of $13,785 after completing their degree.

Curriculum highlights

While WGU divides its program up into “units”, it works in essentially the same way as credit hours, just without the requirement to record a specified number of hours in order to progress. As with many more traditional programs, you’ll end up taking 10 courses in total.

Nine of those courses are in technical topics. Because this is a computer science master’s program with an AI and machine learning specialization, you’ll cover some more general ground before getting into dedicated AI/ML topics: you’ll complete Formal Languages Overview, Computer Architecture and Systems, Applied Algorithms and Reasoning, and Unix and Linux before diving properly into AI specifics. 

The tenth course covers Governance, Risk, and Compliance. This will help ensure you know how to apply AI systems in a way that respects ethical and regulatory security and privacy requirements.

Program Summary

• MS/MEng in Applied Artificial Intelligence
• Estimated tuition: $45,986 per year
• Typical length: 18 months
• Accreditation: MSCHE
• Credits: 30
• Best for: Degree customization, hands-on practice

About the program

Stevens Institute of Technology has a strong reputation for engineering and tech education. It’s a little like Johns Hopkins, in that it has the faculty expertise to be able to offer a wide array of AI concentrations. You can specialize in:

• Artificial Intelligence in Design and Construction
• Biomedical Engineering
• Computer Engineering
• Data Engineering
• Electrical Engineering
• Mechanical Engineering
• Software Engineering
• Systems Biology

This level of specialization, along with a strong institutional reputation, means that SIT graduates are well-placed to enter the workplace. The average Stevens alumni salary is $86,900 within six months of graduation.

Another standout feature of the Stevens program is that you can elect to take it as either an MS or an MEng, each with a slightly different emphasis. You’ll also have the option of a dual-degree MBA, which introduces business and leadership content alongside the AI curriculum.

Curriculum highlights

As well as the significant amount of choice, Stevens’ curriculum stands out for its opportunities for hands-on practice. Two of the tracks are part of the Graduate Cooperative Education Program, meaning you’ll combine your study with periods of paid employment in the field of AI.

If you take the MS route, you’ll also have the choice of a project track or thesis track. SIT stands out as a great place to undertake a thesis, given the high level of faculty expertise and R2 research classification. A thesis is worth 6 credit hours, so if you opt for the project route, you’ll also do an extra elective.

If you go for the Master of Engineering, you won’t have the option of a thesis. Instead, your study will be broken up into 1 mathematical foundation course, 4 core courses, 3 courses in a chosen concentration, and 2 electives. Given the wide range of concentrations, the course list is genuinely fascinating, with highlights including Introduction to Brain-Machine Interfaces and Applied Game Theory and Evolutionary Algorithms.

Taking the program entirely online may limit your choice of courses, but you are able to complete it without any in-person attendance. Stevens provides recommended course sequences for 100% online students.

Program Summary

• MEng in Artificial Intelligence & Machine Learning
• Estimated tuition: $37,500
• Typical length: 1-2 years
• Accreditation: MSCHE
• Credits: 30
• Best for: Accessibility, engineering focus

About the program

Another MEng, the program at George Washington has a highly technical focus. Like most other engineering programs, there’s no thesis option, and the course list is entirely made up of core courses (no electives). You’ll also need a strong engineering background in order to be admitted, with a GPA of at least 3.0 in a relevant bachelor’s degree.

At $37,500, GWU sits in the mid-range of this list on price. And it’s important to make clear that the tuition cost here is all-inclusive. Unlike most other programs, there are no additional fees, and you’ll also get all required software and eBooks provided at no extra cost. 

Admissions are flexible, with 5 start dates available throughout the year (2 in Fall and Spring, plus 1 in summer). There is one scheduled evening class per week, which is designed to fit in with working professionals, although you can choose to enroll full-time and complete the program within a year.

Curriculum highlights

The AI capstone project at GWU will produce something tangible for your portfolio. Under faculty guidance, you’ll be designing AI solutions to real-world problems, and then creating a presentation on what you’ve built.

Before you get to that point, you’ll follow a preset curriculum that equips you with all of the necessary skills. NLP, computer vision, data analytics and autonomous systems are all covered, while you’ll also complete an important law and ethics course.

Courses are available both synchronously and asynchronously, making this a really accessible program for students studying alongside a job. You’ll also have the flexibility to take multiple courses in a term in order to finish sooner.

Program Summary

• Online MS in Artificial Intelligence
• Estimated tuition: $17,985
• Typical length: 2 years
• Accreditation: SACSCOC
• Credits: 33
• Best for: Affordability, AI ethics

About the program

Houston Christian University is one of the more affordable schools on our list. And having only introduced its MS in AI last year, it is currently being billed at a “new program” rate, resulting in an impressive total tuition cost below $18,000.

The downside of it being such a new program is that there is no graduate outcomes data to speak of (an issue with lots of AI programs, in fairness). And HCU doesn’t have an especially prominent national reputation. However, you will graduate with tangible experience to show employers: you’ll have the option of an Applied Learning Practicum, which is effectively an internship. There will also be other collaborative project opportunities through industry partnerships.

As a Christian school, HCU also emphasizes its ethical AI credentials. Like most programs, it has a dedicated AI Ethics course, but it says that principles of ethical stewardship are emphasized across all courses. The admissions policy is fairly generous: STEM degrees are preferred but not required, and GPAs of 2.5-2.99 will be considered on a case-by-case basis.

Curriculum highlights

While the Applied Learning Practicum is undoubtedly a strength of the HCU program, it is not the only pathway to earning your degree. If you want to go down the thesis route, you’re able to do that here. The thesis is designed for “deeper exploration of emerging AI technologies”, offering you the chance to contribute new knowledge to the field. Given the school’s emphasis, anyone wishing to do research grounded in AI ethics should certainly give this option some consideration.

Aside from the choice of final project, the curriculum is fully prescriptive. You’ll take 10 courses, most of which are what you would expect: Machine Learning, NLP, Neural Networks etc. 

However, there is one unique-looking course called Evolutionary and Cognitive Computing. In this, you’ll “explore bio-inspired computing methods including genetic algorithms, evolutionary strategies, swarm intelligence and neural-symbolic systems”. You’ll get the chance to design and implement your own evolutionary algorithms: if that’s an area of interest to you, then you should definitely think about HCU, as you won’t find it in too many other places (and certainly not as part of the core curriculum).

Program Summary

• MS in Information Systems, Artificial Intelligence Track
• Estimated tuition: $45,630 ($28,860 in-region)
• Typical length: 2 years
• Accreditation: MSCHE
• Credits: 30
• Best for: Focus wider than AI

About the program

Unlike most programs in our list, UMBC’s master’s program is not entirely dedicated to artificial intelligence. It is an MS in Information Systems, with the AI element coming via a concentration. You definitely need to be prepared for that before signing up: the AI component is just 9 credit hours, which equates to 3 courses.

However, we have still decided to include it. While the lack of a dedicated AI curriculum will totally rule it out for some people, this alternative route could work for you. A more general education in information systems keeps a lot of doors open, but you’ll still get a grounding in the fundamentals of AI.

UMBC is an R1 university, so it carries a fair amount of prestige. And the slightly less intense AI focus also means it’s more readily accessible to those without technology backgrounds. Admissions are reasonably straightforward, too: you won’t require GRE, and there is no firm GPA requirement.

Curriculum highlights

You can more or less make what you like of UMBC’s master’s program. Obviously you’ll want to take the AI track, but you’re able to take up to two tracks, with 18 of the final 30 credit hours coming from electives.

However, tracks do not appear on your final diploma. So if you’re looking for a program that immediately signals your AI credentials to employers, this is not the one for you. That being said, tracks will show up in your transcript, which is commonly used by employers to verify education.

Within the AI track, you’ll pick 3 courses from the following:

• Data Science
• Deep Learning
• Social Media Application and Analysis
• Special Topics in Information Systems
• Independent Study

The other available tracks are User Experience, Data Science, and Cybersecurity. For final assessment, you’ll have the choice of a thesis, which UMBC recommends for those interested in pursuing a PhD. However, you will need to defend your thesis in person, despite the rest of the program being 100% online.

Program Summary

• Online MS in Computer Science (Data Mining and Intelligent Systems Concentration)
• Estimated tuition: $25,830
• Typical length: 18-24 months
• Accreditation: SACSCOC
• Credits: 30
• Best for: Accessibility

About the program

Like UMBC, the University of Tennessee-Knoxville does not technically offer a dedicated AI program. However, the Computer Science program with a Data Mining and Intelligent Systems concentration certainly warrants its place on the list: when you read through the curriculum, it has just as much AI content as plenty of named programs.

Of course, the name itself may be important to you, because you won’t graduate with an immediately recognizable AI qualification. But if your main focus is on learning the relevant skills, UTK has everything you’ll need.

The program is also well adapted for online learners. All of the program material is available asynchronously, meaning you aren’t tied to any specific hours. You’ll be able to earn the degree in 18-24 months, either full-time or alongside a career.

Curriculum highlights

If you want to, you can essentially turn the UTK Computer Science master’s program into an AI program. Artificial Intelligence and Machine Learning are both core units when you take the Data Mining and Intelligent Systems concentration. You’ll then pick 4 “focused” units, which can include NLP, Deep Learning, Computer Vision, and Reinforcement Learning: all staples of dedicated AI curriculums.

The remaining courses are drawn from wider areas of computer science. But even then, you can pick highly relevant subject matter, like Algorithms, Human-Computer Interaction, and Databases and Scripting Languages. Alternatively, you may welcome the chance to take a slightly broader focus, exploring areas such as Cryptography or Software Security.

For final assessment, you can choose a thesis or a project.

Program Summary

• MS in Artificial Intelligence & Machine Learning
• Estimated tuition: $68,126
• Typical length: 2 years
• Accreditation: MSCHE
• Credits: 45 quarter credits (~30 credits)
• Best for: Curriculum coverage

About the program

Drexel uses the quarter system, which is great for covering a wider array of AI/ML topics. You’ll study 3 core courses and 10 electives over the course of the 2-year MS in program, as well as 2 capstone courses. 

Unfortunately, this approach (along with the fact that this is a private school) comes with increased tuition costs, making Drexel one of the most expensive institutions on our list. You do get a certain amount of prestige for your money (US News and World ranks Drexel joint-80th nationwide, and it is known for computing), but it’s still hard to justify such a high price. It’s more likely to be a realistic option if you qualify for special rates: these apply to military personnel, but also to members of more than 500 partner corporations.

One nice feature of this program is the division into “applied” and “computational” concentrations, the latter having more of a technical focus. If you intend to follow the applied track, your bachelor’s degree does not need to be in a STEM subject. 

Curriculum highlights

The applied and computational tracks diverge straight away: they are almost like separate programs. The core of the applied track is made up of any 3 of the following:

• Introduction to Programming
• Programming Foundations
• Applications of Machine Learning
• Applied Artificial Intelligence

While students on the computational track must all complete:

• Introduction to Artificial Intelligence
• Machine Learning
• Deep Learning

After that, you’ll pick 5 concentration-appropriate electives. If you’re in the applied route, that might include topics like social network analytics, human-AI interaction, and systems basics. Computational courses focus on things like high performance computing, linear algebra, and cognitive systems.

Having said that, there is some cross-pollination of courses across the two concentrations. And you’ll get a further 5 “free electives”, which can come from any graduate-level courses within the Computing and Informatics school.

Sadly, the 6-month coop experience (for an additional quarter credit) is not offered to online-only students. But your two capstone projects will involve developing real AI products, with the help of advisors from academia and industry.

Program Summary

• MS in Computer Science (Artificial Intelligence Specialization)
• Estimated tuition: $70,000
• Typical length: 1-5 years
• Accreditation: WSCUC
• Credits: 45 units (quarter system, ~30 credits equivalent)
• Best for: Academic quality

About the program

A Computer Science MS from Stanford is a big investment, both financially and in terms of time commitment. Completing the program part-time typically takes anywhere from 3-5 years. And although you can finish in as little as 12 months full-time, the online program is primarily geared toward current professionals.

That’s partly because most people will struggle to justify the $70,000 cost, meaning the program is mainly viable for students whose employers have agreed to cover their tuition. There’s nothing to stop you financing it yourself, but you have to ask yourself whether it is really 7x better than the program offered by the University of Texas at Austin.

Having said that, Stanford clearly comes with massive amounts of prestige and academic quality. Times Higher Education ranks it as a top 5 university worldwide, behind only Oxford, MIT, Princeton, and Cambridge. It’s unusual to be able to access that level of quality in a fully-online format, but the AI specialization is one of the few within the Computer Science MS that can be done totally remotely. 

Curriculum highlights

Stanford offers an AI specialization within a CS program, as opposed to a standalone AI program. So you’ll study “foundational” and “breadth” units before getting into AI-focused “depth” units. As such, if you aren’t that interested in wider computer science, this probably isn’t for you.

Having said that, your depth courses will make up at least 21 of your 45 total units. So around half of the program will be explicitly AI-focused, and AI will also clearly be relevant to many of the “breadth” courses too.

The AI concentration focuses on topics like logical reasoning, robotics, machine learning, probabilistic modeling, and natural language processing. To get an idea of what the teaching is like, you can watch the lectures for the entire NLP with Deep Learning course for free on YouTube.

Program Summary

• MS in Data Science and Engineering (AI‑relevant)
• Estimated tuition: $18,780
• Typical length: 1-2 years
• Accreditation: NECHE
• Credits: 30
• Best for: Accessibility and affordability

About the program

The University of Maine’s Data Science and Engineering program does a great job of simplifying the admissions process. It has high academic standards, and you’ll need a GPA of at least 3.0 with at least one college-level statistics course, but you can apply at any time of year and benefit from rolling admissions. You also don’t need GRE/GMAT scores, and if your GPA is a little low, admission is still considered on a case-by-case basis.

Once you’re accepted, Maine stands out for its highly affordable tuition, which works out at just $626 per credit. You won’t be earning a Master’s in AI, and there isn’t even officially a formal AI concentration, but the department has highlighted AI coursework “focus areas” that you can undertake as part of the program. These have a highly technical emphasis, to the extent that you’re expected to have some sort of background in object-oriented design, programming, calculus, statistics and software development in order to enroll. 

Curriculum highlights

Maine’s curriculum structure is a little hard to get your head around at first, but it isn’t as complex as it appears. It’s split up into three categories: Foundation Courses, Theme Areas, and Domain Specializations.

• Foundation courses are primarily meant for students missing certain prerequisites: you’ll catch up on fundamental programming and statistics material. However, you can also include foundation units within your 15 credits of electives.
• Theme areas essentially serve as the equivalent of “core” curriculum, while still giving you some control over what you study. There are 5 different themes, and you must take a course from at least 4 of them (for 12 credits).
• Domain specializations are the equivalent of concentrations. You can tailor your electives in order to graduate with a specialization in one of the following: spatial informatics, bioinformatics, business information, social and behavioral data science, and engineering analytics.

Where things get a little more confusing is that AI is not yet an official domain specialization. However, UMaine suggests suitable course sequences for those interested in this area of study.

The final 3 credits come from a required practicum. You’ll also have the opportunity to complete a summer internship, and students that don’t do so are encouraged to take at least one other course that includes “substantial practical experience” (e.g. a graduate project). 

Program Summary

• Online MS in Artificial Intelligence
• Estimated tuition: $36,330
• Typical length: 2 years
• Accreditation: MSCHE
• Credits: 30
• Best for: STEM focus, electives

About the program

The New Jersey Institute of Technology AI master’s program is designed for people with a bachelor’s degree in the general field of computing. If you don’t have that, but do have an academic or professional STEM background, then you can start with the graduate certificate and then apply to the master’s program. The 12 credits you earn on the certificate will carry over to the master’s degree.

But if you don’t have any kind of STEM background, this program isn’t right for you. The curriculum is heavy on data science and statistics, almost like you’d expect from an MEng. Unlike most engineering programs, however, you do have the option of completing a thesis, which will be overseen by a tenure-track faculty member. In terms of format, NJIT is set up well for online learners. The estimated 2-year completion time assumes that you’ll be studying part time (likely alongside a career), but you can finish sooner via full-time study. When it comes to applying, the College of Computing generally strongly recommends GRE, but it is entirely optional for all applicants to the online program.

Curriculum highlights

The NJIT AI master’s program has a balance of core and elective courses that gives you plenty of choice over your degree plan. Broadly speaking, you’ll do 4 core courses and 6 electives, but that doesn’t tell the entire story.

Even within “core”, you get some level of choice. Probability Distributions and Introduction to Big Data are both mandatory, but you can choose between Artificial Intelligence and Machine Learning for your third core course. For your fourth required course, you’ll actually be picking 1 from a list of 5, so it’s effectively another elective.

The remaining 6 courses are true electives, although NJIT ensures that you get a good wide coverage of topics. You have to take at least 2 data science courses (e.g. reinforcement learning, graph neural networks), you can’t take more than 1 computer science (e.g. computer vision) or statistics (e.g. statistical inference) course, and you’re limited to 2 multi-disciplinary applications courses (e.g. robotics, computational biomechanics).

You don’t actually have to do a master’s project or a thesis, but both routes are available.

Program Summary

• MS in Computer Science with AI Specialization
• Estimated tuition: $48,720
• Typical length: 2-3 years
• Accreditation: SACSCOC
• Credits: 30
• Best for: Computer science with AI focus

About the program

Southern Methodist University’s MS in Computer Science with an AI specialization offers a strong blend of advanced CS training and comprehensive coverage of AI fundamentals. You obviously won’t get through quite as much AI content as you would in a dedicated degree, but you’ll graduate with a widely-applicable degree from a top-100 national school.

The nature of the program means that you’re expected to have very strong computing fundamentals before you enroll. If your bachelor’s degree is not in CS, you’ll need to prove your competence in programming, as well as 6 core areas of computer science. You can do this either through departmental examinations, or completing prerequisite courses.

While the computer science program usually has some in-person elements, you can complete it 100% online if you opt for the AI specialization (although certain electives may not be available to you).

Curriculum highlights

You’ll commit a total of 12 out of 30 credit hours to the AI specialization. 6 of those will be core courses (AI and Machine Learning), and a further 6 will come from a choice of depth electives. Options include Data Mining, Logic Programming, and Information Storage and Retrieval.

The remainder of the program consists of 2 core computer science courses, and 2-4 electives that can be drawn from any of the specializations (software engineering, cybersecurity, theory of computation, or further AI courses). The number of free electives you take depends on whether or not you decide to go down the thesis route.   

Program Summary

• Online Master of Professional Studies in Artificial Intelligence Management
• Estimated tuition: $52,560
• Typical length: 1-5 years
• Accreditation: MSCHE
• Credits: 30
• Best for: Non-technical candidates

About the program

Georgetown University offers the only Master of Professional Studies (MPS) on our list. It’s very important that you understand what that means.

An MPS is far less technical than an MS or an MEng. The AI program focuses on AI strategy, governance, and implementation rather than on building models from scratch. It is designed for professionals who expect to lead AI initiatives, manage AI‑enabled teams, and shape organizational AI strategy, rather than work as hands-on ML engineers.

If you are a technical-minded STEM candidate, then this clearly won’t be right for you. But if you’ve been reading this list and worrying that you don’t have the right background to get an AI master’s degree, then this could be the perfect option. Employers might not immediately recognize the legitimacy of an MPS compared to other types of master’s degrees, but you’ll be able to trade on the prestige of Georgetown, which is ranked in the top 25 universities nationally.

Helpfully, Georgetown lets you try out what it’s like to take an online course via its Canvas platform.

Curriculum highlights

The Georgetown curriculum is laser-focused on what AI means for managers and business leaders. You’ll take six required AI management courses:

• Ethical AI: Moral Dilemmas and Biases
• Introduction to AI
• Innovation Management and AI Strategy
• AI Governance and Compliance
• Communication Strategies for Digital Transformation
• Capstone

The remaining electives come from one of two focus areas: AI Strategy and Leadership, and AI Development and Integration. You can tailor your path depending on exactly how you’re expecting to encounter AI as a manager in the workplace. 

Program Summary

• M.S. in Emerging Technologies
• Estimated tuition: $75,750
• Typical length: 2-3 years
• Accreditation: MSCHE
• Credits: 30
• Best for: Interdisciplinary study

About the program

There’s no getting away from the fact that NYU offers the most expensive AI master’s program on our list. But with the immediate proviso that it will probably only be an option if you have some kind of external funding or full scholarship, the program itself is worth your consideration.

You’ll officially graduate with an MS in Emerging Technologies, although the faculty’s own website describes the program as an “AI degree”. One of its main strengths is that you can really dive into the applications of AI and other new technologies within your specific field: you’ll work with a dedicated advisor to create a degree plan that’s highly relevant to your needs.

That flexibility also means that there are no specific prerequisites you need to fulfill before you can enroll. Some concentrations will require a more technical background, but the program is theoretically open to all. 

Curriculum highlights

The online program at NYU is broken down into seven concentrations. One of them is Machine Learning and Artificial Intelligence, but you don’t actually have to opt for that one to get a valuable AI education.

Taking the AI/ML concentration will get you the most typical AI program (and will require a technical background). But the biggest USP of this program is how interdisciplinary it is. In each of the concentrations, you’ll be looking at how AI and other new technologies are impacting a specific field. The options are as follows:

• Machine Learning and Artificial Intelligence
• User Experience and Design
• Innovation and Change Management
• Data Science
• Cybersecurity
• Urban Informatics
• Wireless & Networking

Each concentration is made up of 12 credits, and comes with its own capstone course. Regardless of the concentration you choose, you’ll also take 6 credits of required AI courses, and 12 credits of interdisciplinary electives. 

NYU encourages “experiential learning”, and you can earn up to 9 credits through things like projects, guided studies, or a thesis.