The 5 Best AI Masters Degree Programs in Washington
AI masters degree programs in Washington state are opening doors to exceptional career opportunities, with graduates securing starting salaries exceeding $110,000. The job outlook is impressive. Machine learning engineer and AI specialist positions are projected to grow 23% through 2032, and the state expects nearly 4,000 new roles for AI professionals each year until 2031.
Washington’s universities provide a variety of options, whether you’re interested in a Masters in AI and Machine Learning or an AI Engineering masters. Our list explores the five best programs and helps you choose the right fit for your career goals.
1. University of Washington – Master of Science in AI and Machine Learning for Engineering
Program Overview
UW’s Master of Science in AI and Machine Learning for Engineering stands apart as a stacked degree program built for working engineers who want to advance their careers through practical AI applications. The program uses a flexible certificate-stacking model where you begin with a foundational graduate certificate, add a second domain-specific certificate, and complete an applied capstone project to earn your master’s degree.
This structure lets you tailor your education to match your schedule and budget. You can enroll part-time and take certificates one at a time, or pursue them as a full-time student. All stackable certificates are available part-time, so you maintain the flexibility to work while studying.
The program targets engineers applying AI and machine learning methods to fields with physical constraints, such as manufacturing, chemical processes, or robotics. You’ll complete domain-specific training to learn state-of-the-art techniques relevant to your particular field beyond foundational AI skills applicable in any discipline.
Applications open each January, with a June 1st deadline for fall admission. One restriction applies: the program isn’t eligible for F1/J1 international students requiring an I-20/DS-2019 to enroll at UW. Non-U.S. citizens in the U.S. who don’t require these documents can be admitted, though. Students wishing to complete the degree via online certificates while remaining outside the United States are eligible to apply.
Key Curriculum Features
The certificate-stacking approach offers strategic flexibility for your career development. You start by enrolling in the Graduate Certificate in AI and Machine Learning for Engineering, which builds your foundational knowledge. This certificate covers core AI and ML concepts that engineers in any discipline need to understand.
You select from domain-specific options that line up with your engineering specialization for your second certificate. These discipline-specific certificates include areas like Data-Driven Dynamic Systems and Control for Engineering, or Data Analytics for Systems Operations, depending on your field.
Faculty teaching these programs bring expertise in both machine learning and traditional engineering disciplines such as robotics, materials, dynamics and control. This dual expertise means you learn how AI integrates with established engineering principles rather than studying it in isolation.
The program ends in a two-quarter applied capstone project where you demonstrate knowing how to apply AI and ML techniques to real-life engineering challenges. This hands-on component means you graduate with practical experience beyond theoretical knowledge.
Certificates can be taken one after another, so you gain professional value upon completing each one. Your credentials strengthen as you advance toward the full master’s degree, allowing you to utilize new skills in your current role before finishing the entire program.
Admission Requirements
The program requires a 3.0 cumulative grade-point average on a 4-point scale from an accredited school. You need an undergraduate or graduate degree from an accredited institution meeting this GPA threshold.
Prerequisite coursework has calculus, differential equations, linear algebra, and physics from your undergraduate studies. You also need either undergraduate coursework or work experience with writing computer code in any programming language.
The program recommends having majored in engineering, physics, chemistry, or a related discipline in your previous degree. Other majors will be considered if you’ve completed the required prerequisite coursework.
Non-native English speakers not already enrolled in a UW graduate program must demonstrate English language proficiency according to Graduate School Policy 3.2.
Application materials include:
- Transcripts from all colleges and universities attended (unofficial for application, official if offered admission)
- English-language translations of transcripts if originals weren’t in English
- One-page resume listing relevant professional experience and community contributions
- One-page statement of purpose describing how this degree program would help reach your professional goals
- One letter of recommendation from a current or recent supervisor or instructor
The program doesn’t require the GRE. If you’ve been out of school for more than five years or your most recent degree isn’t in a related subject, use your personal statement or resume to highlight how you’ve maintained your math and coding skills through work or continuing education.
Tuition and Financial Aid
The total cost estimate for the degree ranges between $40,375 and $43,088 for 2025-26. The exact amount depends on which domain-specific certificate you select for your second certificate, as different specializations carry varying costs.
This estimate is subject to change if individual certificate rates adjust in future years. You can spread the curriculum over a longer period, which offers the financial advantage of distributing costs over time. Most students take a year or more to complete a certificate and two to four years to complete their degree.
This extended timeline allows you to work within your budget and take advantage of employer funding or tax benefits that may offset some costs. You can manage expenses while continuing to earn income by making steady progress toward your certificates and degree.
Financial support options include employer funding, which many companies provide as full or partial tuition reimbursement. Student financial aid is available to eligible students. The stacked structure provides the flexibility to stop and start as needed, helping you complete the program at a pace that lines up with your financial situation.
Career Outcomes and Industry Connections
UW Engineering maintains strong industry connections that benefit graduates of AI masters degree programs Washington offers. The Career Center at Engineering recorded 14,742 student interactions in AY24, including more than 5,000 one-on-one interactions with staff. Approximately 2,500 companies recruit students through the center.
UW Engineering graduates achieve a positive outcome rate of 85%, with more than 66% of students finding full-time employment within six months of completing their degrees. More than that, 82% of graduates stay in Washington state after graduation.
Top employers hiring the largest number of UW Engineering graduates include Amazon, Boeing, University of Washington, and Microsoft. These companies recruit from UW programs and maintain ongoing partnerships with the university.
The Boeing-UW collaboration shows these industry connections. Boeing and UW have partnered on physics-based AI and machine learning for over a decade, with Boeing’s Director for the University of Washington relationship overseeing education and research collaborations.
Microsoft and UW expanded their partnership in 2026 to prepare Washington state residents for an AI-driven economy. This initiative increases UW’s access to advanced AI computing, broadens internship and applied research opportunities, and develops community AI literacy programs. Microsoft representatives have expressed interest in creating opportunities for 1,000 more people through research marketplaces and internships.
Faculty across UW’s Mechanical Engineering department work to develop fundamental AI and machine learning technology for dynamic systems, apply that technology to real-life problems, and shape educational and workforce development pathways. This research informs curriculum development and creates additional opportunities for students to involve themselves with state-of-the-art applications.
2. Seattle University – Online MS in Artificial Intelligence
Program Overview
Seattle University’s Online MS in Artificial Intelligence distinguishes itself through a commitment to ethics and responsible innovation among technical mastery. This 49-credit, fully online program prepares students for advanced AI roles through asynchronous courses and a two-year completion timeline. Recent graduates, working tech professionals, and those pivoting from related fields will find the flexible structure accommodating.
The multidisciplinary curriculum spans computer science, machine learning, data science, and human-centered design. You gain technical foundations with this approach while emphasizing ethical considerations that separate responsible AI leaders from those focused solely on algorithms. Seattle University’s strong connections to top Seattle-area employers position graduates where AI transforms industries from health care to finance.
Students gain skills to design, develop, and maintain AI systems through ground applications. The program delivers a resilient curriculum designed to transform students into skilled innovators, responsible designers, and ethical leaders in AI-powered systems. You apply skills to tackle complex AI challenges through engaging real-world projects and emerge as an adaptable and forward-thinking leader.
The program does not support F1 Visa for international students. But the fully online format allows flexibility for domestic students to complete coursework while maintaining employment.
Key Curriculum Features
The curriculum centers on ten required courses covering core AI competencies and advanced specializations. Required coursework has Artificial Intelligence, Machine Learning, Advanced Machine Learning, Big Data Systems, AI Systems, AI Governance, Ethics and Philosophy of AI, Generative AI and LLMs, and AI Capstone Projects. You complete either Computer Vision or Natural Language Processing as your final required course.
Four elective options allow specialization aligned with your career interests. AI and Machine Learning for Cybersecurity, Numerical Methods for Machine Learning, Data Visualization, and Social Network Analysis provide targeted expertise beyond core requirements.
The Industry Advisory Board plays a vital role in shaping the curriculum. The board cooperates with faculty to ensure coursework reflects current trends, emerging technologies, and evolving employer needs. Experienced leaders across the tech industry compose the board. Board members strengthen connections between classroom learning and workplace applications through ongoing partnership and support student learning and career pathways.
The three-quarter capstone through Seattle University’s Project Center offers hands-on experience with industry-sponsored AI projects. You apply classroom learning to real-world challenges while building connections with employers across the region and work in small teams. You graduate with practical skills beyond theoretical knowledge because this experiential component will give a solid foundation.
You master core areas of artificial intelligence and advanced knowledge in state-of-the-art areas of the field at graduation. You understand AI literature with sufficient mathematical and analytical maturity to maintain professional currency, convey technical material through formal written papers and oral presentations, and apply appropriate AI concepts to solve real-world problems while exhibiting awareness of relevant ethical and social considerations.
Admission Requirements
Seattle University welcomes students from diverse educational backgrounds but requires previous coursework in statistics, integral calculus, and Python programming. Graduate Admissions accepts and reviews applications on a rolling basis, with materials submitted by the stated deadline for each quarter.
The university waives the application fee for all applicants and removes financial barriers to graduate education. Application materials have a completed application for graduate admission, official transcripts of all post-secondary institutions attended in the last 90-quarter/60-semester credits of the bachelor’s degree, academic background verification, and a resume or CV. You can use unofficial transcripts during the admissions process if official transcripts are unavailable.
Academic prerequisites have Elementary Probability and Statistics (equivalent to MATH 1210, MATH 2310, or ECON 2100), a programming course in Python (CPSC 1220), and Integral Calculus (MATH 1334-1335). Courses covering probability, confidence intervals, hypothesis testing, and regression satisfy the statistics prerequisite. Calculus-based courses are strongly recommended.
You complete one of three options for Python proficiency: a university-level course using Python as the primary language, approved online courses that have Google’s Crash Course in Python or MIT’s Introduction to Computer Science and Programming Using Python, or Seattle University’s online Python placement exam.
Integral calculus courses should cover integration, u-substitution, and integration by parts. Students may complete equivalent courses at community colleges or regionally accredited institutions and online options are available.
Most students do not need the GRE. Students subject to the 3-year degree policy or who earned degrees from institutions issuing non-graded transcripts must submit official GRE or GMAT results.
Tuition and Financial Aid
The MS in Artificial Intelligence charges $1,073.00 per credit with 49 total program credits required for the 2026-27 academic year. Mandatory enrollment fees have a $175.00 matriculation fee charged during the first term, a $172.00 quarterly wellness fee, a $214.00 quarterly technology fee, and a $20.00 quarterly graduate activity fee.
The matriculation fee offsets costs of maintaining and storing academic records. The wellness fee provides funding for health and wellness resources benefiting all students and has TimelyCare access, university fitness center access, and online and in-person health and wellness programs. The technology fee assists with core student systems like Canvas, mySeattleU, Microsoft Office, Public Safety systems, Internet service, and networking. The graduate activity fee allocates funding for graduate programs that have residencies, accreditation, and supplies used during class sessions.
New graduate students pay an enrollment deposit of $250.00 to confirm intended enrollment. This applies toward your first tuition bill rather than serving as an additional fee.
Financial aid counselors help students find resources to pay for education and these have grants, loans, work study, and scholarships. Seattle University offers military tuition discounts for active-duty servicemembers and their spouses as a Yellow Ribbon school and accepts military benefits such as the Post 9/11 GI Bill and Tuition Assistance.
Career Outcomes and Industry Connections
Graduates pursue careers with companies that have Google, Microsoft, Meta, and Amazon. The program prepares you for leadership roles through collaborative projects, research, and real-time challenges from corporate partners.
The Bureau of Labor Statistics expects most important job growth in areas requiring masters in AI and machine learning concentration by 2028. Professionals with a master’s degree earn an average of 20 percent more than those with only a bachelor’s. The Washington Employment Security Department projected nearly 4,000 annual new roles for AI professionals in Washington state until 2031 in 2024.
The Project Center aids industry connections through three-quarter capstone projects where students work with partner companies on real challenges. This experiential approach builds professional networks before graduation and creates direct pathways to employment opportunities.
Seattle University’s mission emphasizes preparing leaders for a just and humane world, with programs understanding ethical and legal aspects of technology. The curriculum prepares you to drive innovation responsibly and equitably from learning public policy and societal effect of information technology to ensuring compatibility with social justice values and ethical implementation.
3. City University of Seattle – Master of Science in Artificial Intelligence (MSAI)
Program Overview
City University of Seattle’s Master of Science in Artificial Intelligence targets working professionals who want to advance their technical expertise without pausing their careers. The 39-59 credit program provides complete foundations in AI theory and practice and gives students the skills to develop and deploy ethical, human-centered artificial intelligence techniques for real-life applications.
The credit range accounts for preparatory courses that some students need before starting core coursework. Students entering without sufficient technical background in programming, databases, networking and operating systems complete foundational courses first. This structure makes AI masters degree programs Washington more available to professionals transitioning from adjacent fields.
The curriculum emphasizes practical expertise with theoretical knowledge. Core courses span AI programming, discrete math and algorithms, machine learning and deep learning, natural language processing, agent-based systems and cloud computing. The program concludes with an applied capstone project that simulates real-life experience and ensures you graduate ready to tackle industry challenges.
CityU designed this program to prepare graduates who can apply foundational AI knowledge, implement principles to use cases, analyze problems using critical and ethical thinking, evaluate data for informed decisions, communicate ideas across delivery modes and work together on diverse teams.
Key Curriculum Features
The program requires 24 core credits that cover foundational and applied AI concepts. Students begin with CS 500, a zero-credit orientation course taken during the first quarter of enrollment. Core coursework has Artificial Intelligence Overview, AI in Cloud Computing, Natural Language Processing, Programming for Computing, Discrete Math and Algorithms, AI for Data Science, Machine Learning & Deep Learning and Math & Statistics for Data Science.
Depth of study adds 6 credits through Agent Based Systems and Emerging Topics in Artificial Intelligence. These courses explore specialized applications and state-of-the-art developments in the field.
You select two courses from any graduate offerings within the School of Technology & Computing for electives. You can also complete an internship after taking three CS 650 seminar courses for internship preparation. Each seminar enrollment requires pre-approval from the Program Manager.
The culminating experience offers two pathways: the AI 680 Artificial Intelligence Internship or the AI 687 Artificial Intelligence Capstone. Both options provide hands-on application of classroom learning to real-life scenarios.
Admission Requirements
Applicants need an earned bachelor’s degree plus evidence of completion in four technical areas. You demonstrate equivalency of 5-quarter hour credits at the intermediate level in at least one computer programming language, 5-quarter hour credits in networking that covers TCP/IP from physical through applications layers, 5-quarter hour credits of data management that has database design and SQL/NoSQL queries, and 5-quarter hour credits of operating systems that has OS theory, process management and memory management.
An alternative pathway exists for those lacking these prerequisites. You can complete CityU’s Undergraduate Certificate in Foundations of Systems Development instead of meeting individual course requirements.
Preparatory courses have CS 132 Computer Science I, CS 330 Network Communications, CS 340 Operating Systems and IS 360 Database Technologies, each carrying 5 credits. These courses establish the technical foundation necessary for graduate-level AI coursework.
Tuition and Financial Aid
The quarterly cost of attendance varies based on living arrangements for 2026-27. Students living with parents face estimated quarterly costs of $4,840, while those not living with parents see costs of $7,850. These estimates have tuition, fees, supplies, housing, food, transportation and personal expenses.
Supplies average $176 per quarter and cover books, course materials and equipment. Housing costs range from $1,278 for students living with parents to $4,216 for independent living arrangements. Food costs $1,870 quarterly whatever the housing situation.
Financial aid counselors help identify resources that have grants, loans, work study and scholarships. CityU offers military tuition discounts for active-duty servicemembers and their spouses as a Yellow Ribbon school and accepts Post 9/11 GI Bill and Tuition Assistance benefits.
Google employees receive a 15% tuition discount on CityU’s 65+ degree and certificate programs, with the MSAI listed among popular options for Google staff. The university also partners with organizations like the American Bankers Association and offers employees of ABA member associations a 15% tuition scholarship.
Career Outcomes and Industry Connections
CityU alumni report strong career outcomes after graduation. About 9 out of 10 graduates have jobs, with 74% working in their degree field. More, 86% of alumni saw a salary increase within two years of graduation, with the average increase reaching 58%.
Top companies hiring CityU graduates have Amazon, Boeing, Google, Accenture, YouTube, Microsoft, Starbucks, T-Mobile, Seattle Public Schools, The Walt Disney Company and United States Department of Defense. These employers value the practical skills and ethical AI framework emphasized throughout the program.
The MSAI prepares you for roles such as Machine-Learning Engineer, MLOps/AI Platform Engineer, AI Software Engineer, AI Systems Architect, Responsible-AI & Ethics Specialist and AI Product Manager. Graduates work across industries that have healthcare AI diagnostics, manufacturing predictive maintenance, education personalized learning AI, finance algorithmic trading, green energy smart grid optimization and broader technology sector innovation.
Alumni satisfaction remains high, with 8 in 10 reporting they are somewhat or very satisfied with their overall college experience. Flexibility and convenience of the program rank highest in satisfaction at 91%, followed by development of knowledge and skills at 84%.
4. Eastern Washington University – MS in Organizational Leadership with AI Leadership
Program Overview
Eastern Washington University offers a distinct path among ai masters degree programs washington provides through its MS in Organizational Leadership with AI Leadership concentration. This program bridges human insight with emerging technologies rather than focusing on technical skills alone. You’ll learn to lead teams and organizations in AI-integrated environments.
The 44-credit program runs online through accelerated six-week courses. You can complete it in as few as 10 months. Seven start dates per year provide flexibility for working professionals. Upcoming sessions begin July 6, September 21, November 2, December 28, and February 8. The pay-per-course structure lets you control costs and how fast you move through the curriculum.
Students learn about AI ethics, communication with emotional intelligence, and data-informed decision-making. They also study organizational culture before finishing with a capstone focused on AI-driven leadership. The Eastern Washington University School of Business holds AACSB International accreditation. This places it among an elite group of business schools worldwide.
Key Curriculum Features
The curriculum spans nine required core courses totaling 36 credits. You begin with Foundations of Leadership, Social and Emotional Dimensions of Leadership, and Ethical Leadership. Later coursework covers Organizational Theory and Culture, Organizational Communication and Conflict Resolution, Leadership for Social Justice, Leading Change, Leadership for a Better World, and a Leadership Capstone.
The AI Leadership concentration adds 8 credits through two specialized courses. LEAD 550: Artificial Intelligence in Leadership looks at AI’s role in improving individual leadership effectiveness. You’ll learn about tools and methodologies that improve decision-making, team leadership, and collaboration. You’ll guide teams through ethical challenges including bias and accountability while balancing technology with human-centric practice.
LEAD 551: AI and Organizational Transformation analyzes how AI transforms organizations and societal systems. You’ll get into AI-driven change management strategies and integration of AI technologies at organizational levels. The course also covers assessment of associated risks and opportunities. It emphasizes your role in promoting innovation and managing workforce transitions while ensuring responsible AI implementation.
Both concentration courses require LEAD 501 completion and admission to a Leadership degree program as prerequisites.
Admission Requirements
You need a bachelor’s degree from a regionally accredited institution with a cumulative 3.0 GPA. Additional materials include a professional resume and official transcripts from the college or university where you earned your degree.
The program considers applicants with GPAs below 3.0 on a case-by-case basis if they have at least 3 years of professional work experience. The program waives GMAT requirements for qualified applicants. This removes barriers for experienced professionals returning to graduate education.
Tuition and Financial Aid
The program charges $345 per credit hour. This translates to $1,380 per four-credit course. Total program cost reaches $15,180 for the complete 44 credits. An application fee of $75 applies to new students.
EWU provides the same affordable tuition rate for all in-state and out-of-state students. This eliminates geographic cost disparities common in graduate education. Foundation courses, if required, add to the total program cost.
Career Outcomes and Industry Connections
Graduates pursue roles including Business Intelligence Analyst, Supply Chain Manager, Management Analyst, Operations Director, Data Analyst Director, Financial Analyst, and Marketing Manager. These positions blend leadership expertise with AI proficiency. They reflect the program’s dual focus on organizational leadership and technological integration.
The program gives you the skills to assess AI tools for improved decision-making and organizational transformation. This positions you for masters in ai and machine learning leadership roles in industries adapting to AI-driven business models.
5. University of Washington – Paul G. Allen School MS in Computer Science & Engineering with AI Focus
Program Overview
The Allen School ranks among the top ten computer science programs nationwide. Faculty lead AI research in natural language processing, computer vision, robotics and machine learning. The Professional Master’s Program (PMP) offers an MS in Computer Science & Engineering where you can focus your studies on AI topics through specialized coursework and research opportunities.
This self-sustaining, fee-based program operates as a part-time pathway designed for working professionals. You enroll in 4-5 credits per quarter while maintaining employment. The program requires 40 credits total and does not support F-1 or J-1 student visas, though international students holding other visa types that allow part-time study are welcome.
Key Curriculum Features
The Allen School offers extensive AI coursework including Machine Learning (CSE 446), Natural Language Processing (CSE 447), Computer Vision (CSE 455), Artificial Intelligence (CSE 473), Autonomous Robotics (CSE 478) and Deep Learning (CSE 493G1). Faculty expertise spans AI subfields. Courses scrutinize technical aspects and ethical implications through offerings like Computer Ethics Seminar (CSE 480).
Working professionals interested in graduate-level AI coursework can explore the Graduate Certificate in Modern AI Methods, a stackable credential covering deep learning, computer vision and natural language processing applications. The curriculum adapts faster as faculty integrate innovative developments and positions students to build with AI rather than compete against it.
Admission Requirements
You need a four-year baccalaureate degree from an accredited institution with a minimum 3.0 GPA. The average admitted student holds a 3.5 GPA, though the program reviews complete academic histories rather than only cumulative GPAs. The PMP does not require the GRE. Submitted scores will not be referenced during application review. Non-native English speakers must demonstrate proficiency through TOEFL scores of 92 or higher (4.5 for tests after January 21, 2026), IELTS scores of 7.0, or Duolingo scores of 125.
Tuition and Financial Aid
The per-credit rate stands at $1,140.02 as of autumn 2026. The typical program cost reaches $45,680 with 40 required credits. Quarterly costs average $5,710 for 5 credits, with an additional $295 per quarter for student fees including U-PASS, technology infrastructure and IMA recreation facility membership. Federal financial aid and VA benefits are available to eligible students. Many employers provide tuition reimbursement, though Washington state employee tuition exemption does not apply to fee-based programs.
Career Outcomes and Industry Connections
Allen School partnerships with Microsoft, NVIDIA and Amazon create direct pathways to industry opportunities. The Microsoft collaboration expanded in 2026 to increase access to advanced AI computing, broaden internships and develop AI literacy programs statewide. The UW-Tsukuba partnership supported by $110 million from NVIDIA and Amazon advances AI research in healthcare, robotics and climate science. Faculty research informs curriculum development and ensures graduates emerge as adaptable problem-solvers ready for AI-driven industries.
Next Steps
Washington’s five AI master’s programs each serve distinct career paths. You can choose engineering-focused AI through UW’s certificate-stacking model, ethics-centered training at Seattle University, available technical foundations at City University, leadership skills at Eastern Washington, or research depth at the Allen School. Each program matches different goals.
Starting salaries exceed $110,000 and job growth projections show 23% increase through 2032. This is a big deal as it means that the investment proves worthwhile. Strong industry partnerships with Amazon, Microsoft and Boeing create direct pathways to employment.
Review each curriculum against your career objectives and identify which program arranges with your background and aspirations. Then take the next step toward becoming an AI professional.