The Master of Science in AI & Machine Learning for Engineering

How to apply

To be eligible to apply to the Master of Science in AI & Machine Learning for Engineering, one of the following must be true: 

• You are a part-time student currently enrolled in a base (Component 1) or discipline-specific (Component 2), and are applying to your second certificate 

• You have previously completed a base or discipline-specific certificate, and are applying to the second certificate 

• You are a full-time student applying to the Master of Science in AI & Machine Learning for Engineering and both of your certificates at the same time. 

Part-time students can apply to the master’s degree at the same time as applying to their second certificate, or after being admitted to their second certificate.

Full-time students apply to the degree at the same time as applying to both certificates.

Admission requirements

The University of Washington's minimum criteria represent the requirements an applicant must meet to be eligible for admission to a graduate program.

For more information, reference the UW Graduate Schools' minimum admission requirements. This program does not require the GRE.

This master’s program is not eligible for F1/J1 international students who require an I-20/DS-2019 to enroll at UW. Non-U.S. citizens in the U.S. who do not require an I-20/DS-2019 to study and have the ability to be a student, can be admitted to the master’s degree. Students wishing to complete the master’s degree while remaining outside of the United States are eligible to apply. Students in that situation may want to contact ai4eng-advising@uw.edu to understand access options and requirements for synchronous participation. 

Application process

To complete this master’s degree, you will combine two different graduate certificates together and complete a capstone project. The master’s degree you receive is the same as any other master’s degree – you just apply slightly differently. 

Part-time application

To apply part-time to the Master of Science in AI & Machine Learning for Engineering, you only need to apply for your base certificate in your first year. This means you will first apply to the Graduate Certificate in AI & Machine Learning for Engineering only.   

You will then apply for the master’s degree at the same time as applying to your second certificate, or after being admitted to your second certificate. This can be done while you are enrolled in the Graduate Certificate in AI & Machine Learning for Engineering, or at a later point.  

Your application to the Graduate Certificate in AI & Machine Learning for Engineering will be submitted through the UW Graduate School’s online application system. 

Apply as a part-time student

Full-time application 

To apply full-time to the Master of Science in AI & Machine Learning for Engineering, you must apply to all three application components at the same time.  Full-time applicants will submit three separate applications in the same year, before the Master’s degree application deadline: 

1. An application to the Graduate Certificate in AI & Machine Learning for Engineering 

2. An application to a discipline-specific certificate, and 

3. An application to the Master of Science in AI & Machine Learning for Engineering. 

All applications are submitted through the UW Graduate School’s online application system. 

Apply as a full-time student

Steps to apply

Create an account in the UW Graduate School’s online application portal. We recommend using a personal email address rather than a school or work email to ensure that you have an active secondary contact email address on file throughout your association with UW. 

To start your application to the Master of Science in AI & Machine Learning for Engineering, select ‘Graduate’ for your application type. Then, filter by campus (Seattle) or by degree (master’s), and select Engineering Stacked Degree - AI & ML for Engineering (Master of Science) from the list of programs. For applications to the participating graduate certificates, please refer to their websites for information on how their certificates are listed in the application system. 

Profile information: Take care to ensure this information is accurate, with particular attention to the questions regarding citizenship, residency, and whether you are a native English speaker. 

Contact information: Enter your current and permanent addresses. 

Academic history: Report each higher education institution you have attended and your dates of attendance. 

Application materials

Transcripts

For each school, upload unofficial copies of your transcript and report your cumulative GPA. For support converting an international GPA to the 4-point scale, you may use Scholaro’s free calculator. 

For the school(s) where you have previously earned a degree, your documents must indicate the degree and when it was awarded. Transcripts and marksheets often indicate this information. If your transcript and degree statement were issued separately, then please combine your unofficial copies into one file before uploading. 

If your transcripts are in a language other than English, please have them translated and upload the translated versions in your application. 

Official transcripts are not required during the application process; you will only have to submit official documents to UW if you accept an admission offer. At that time, you should provide your documents according to the Graduate School’s official transcript requirements. 

Resume

1-page resume: including lists of relevant professional experience and contributions to the community through volunteering and service. 

Statements and letter of recommendation

1-page statement of purpose that should describe how this program would help the prospective student reach their professional goals in their current and/or potential future work. Make sure to elaborate on career goal alignment and potential future benefits to the community that you feel your work could provide. If you do not meet some or all of the minimum requirements, please use the personal statement to address these issues. 

One letter of recommendation. This should be from a current or recent supervisor or instructor. The letter should speak to the applicant’s anticipated ability to complete graduate-level technical assignments and other professional skills such as working as part of a team and meeting deadlines. 

Application fee

In the “Application Questions” part of your application, you will be asked to indicate whether you are, or ever have been, enrolled in one of these programs: AI& Machine Learning for Engineering stacked degree, Multidisciplinary Masters of Engineering, or Leadership and Systems Innovation (this includes another graduate certificate that can count toward this stacked master’s degree).

• Answer no if: you are applying only to the Graduate Certificate in AI & Machine Learning for Engineering, have no other affiliation with a stackable certificate or degree, and plan to pursue this program part-time.
• Answer yes if: you are applying to the Master of Science in AI & Machine Learning for Engineering as a full time student and are submitting your application to the Graduate Certificate in AI & Machine Learning for Engineering at the same time that you are applying to our stacked master’s degrees OR you are applying planning to complete the Master of Science in AI & Machine Learning for Engineering as a part time student and you have previously been enrolled in or completed another stackable graduate certificate.

If you answered no to the above question, you will be taken immediately after clicking to submit an application to the TouchNet payment portal to pay the $90 non-refundable application fee (this fee is retained by the UW Graduate School and is collected for all graduate program applications at UW). Pay the fee to finalize your application.

Students enrolled in stacked degrees will only pay for one application fee for their three applications.

After you apply

The Master of Science in AI & Machine Learning for Engineering has an application deadline of June 1^st. All application reviews take place after the deadline passes. The day you submit your application does not affect your chances of admission.

Applicants will be notified of the outcome of their applications 4-5 weeks after the application deadline, via an email to the address associated with their application account.

Admitted students

Students who accept their admission offer will receive further instructions regarding their onboarding process, course registration, and orientation to the Master of Science in AI & Machine Learning for Engineering. Some required steps for all incoming students include:

• Sending official transcripts to the UW Graduate School. More information about this will be found on your application portal if you are admitted.
• Completing short online courses on Title IX and civil rights.

Program cost and financial support

Pursuing a stacked master’s degree is an investment in your short-term and long-term future. The return on your investment may begin to be realized upon completion of the first certificate, immediately bolstering your professional credentials for a career opportunity.

Most students will take a year or more to complete a certificate and two to four years to complete their degree. Spreading the curriculum over a longer period of time has a financial advantage of distributing the program’s cost over time.

Making steady progress towards a certificate and degree allows students to work within their budget and take advantage of employer funding or tax benefits that may be available to offset some of the cost. Additionally, stacked degrees and certificates allow you to stop and start as needed to complete the program.

Calculate your program cost

The exact cost of this degree will depend on which certificates a student chooses to combine into their master’s degree. To calculate the potential cost of your degree, you will need to add the cost of your chosen base/ component 1 + the cost of your chosen discipline-specific certificate/ component 2 + the cost of your 8-credit capstone course. You will also be responsible for a small quarterly fee that the university charges, which varies based on the number of credits per quarter. For 2025-2026, capstone credits are $1,030 per credit. 

In 2025-26, the total cost estimate for the degree is between $40,375 and $43,088. This estimate is subject to change if individual certificate rates change in future years. 

Financial support

Explore these various sources of financial support including employer funding and student financial aid.

Application tips

These are tips for preparing a strong application for the UW Graduate Certificate in AI and Machine Learning for Engineering. These tips have been provided by our program staff and faculty who have reviewed applications for the program. Because they are based on applications from many different people, some tips may not apply to you.  

Prerequisites 

These are tips for preparing a strong application for the UW Graduate Certificate in AI and Machine Learning for Engineering. These tips have been provided by our program staff and faculty who have reviewed applications for the program. Because they are based on applications from many different people, some tips may not apply to you.  

A major factor in application reviews is whether applicants are sufficiently prepared for the math and coding used in classes.  

• If you have been out of school for more than 5 years, or if your most recent degree is not in a relevant subject, use your personal statement or resume to highlight how you have kept up your math and coding skills, for example through work or continuing education. If you don’t use math and coding in your current work, consider taking a course at UW as a graduate non-matriculated student to brush up on skills.  
• If you received low grades in prerequisite courses or are missing prerequisite courses on your transcripts, use your personal statement to explain how you have gained or strengthened these skills through your career or continuing education. If you have not taken the prerequisite courses, consider taking them at UW as a non-matriculated student.  
• If it might be unclear which courses meet the prerequisite requirements, for example, if your transcript lists “Engineering Math II” instead of “Differential Equations”, provide context for the application reviewers so they can easily confirm that you meet the prerequisites.  
• If you received any previous degrees from a school outside the US, provide an English-language translation of your transcripts if the originals were not in English. Also take note of the tip above about providing context for course names for prerequisites.  
• If you transferred schools (for example, started at a 2-year school), provide transcripts from all schools you attended. This is particularly important if you took the required prerequisites while at your first school.  
• If you do not have transcripts or a grade for a required prerequisite, please use your personal statement to provide details on why your application should be considered despite the missing prerequisite. For example, if you took a non-credit course through Coursera or Khan Academy, describe the material covered and any evidence you can provide that you completed the assignments and mastered the topics. Or if you learned the material in your workplace, be specific about whether it was through formal on-the-job training or self-taught, with evidence that you have mastered the material and use it in your job.

Career goal alignment 

There are many different types of AI and machine learning algorithms and applications, and we want to ensure that the students we admit will benefit strongly from our curriculum. To help the reviewers understand why our curriculum is a good fit for your career goals: 

• Provide specific examples of how your current or future engineering projects relate to our curriculum. 
• If you are currently working in a relevant field, pointing to recent work that is related to our curriculum can be helpful. 
• If you are currently working in a different field or in a field that may not be obviously relevant, it is especially important for you to explain: 
  • Whether you hope to move your career in a new direction based on the skills and knowledge gained in our program, or 
  • How your current work is relevant to our curriculum, even if it may not be obvious to the reviewers. If you currently work as a software engineer or business analyst, this tip especially applies to you.

Remember that reviewers aren’t necessarily in the same field as you. Use language that someone from any engineering discipline outside your current employer would understand. Spell out all acronyms, and avoid jargon. Provide context for job titles. 

Benefits to the community 

We consider both how our program can benefit the applicant and how the applicant could use the skills they gain to contribute to the larger community. These contributions include: 

• benefits to the global engineering community (for example sharing of knowledge or development of new techniques), 
• benefits to humanity, 
• benefits to the applicant’s current or future employers.