Image representing Artificial Intelligence and Machine Learning

Engineering MS: Artificial Intelligence and Machine Learning
MS

Our Artificial Intelligence and Machine Learning Masters is a one-of-a-kind program combining AI skills with engineering, open to students with or without an engineering or computer science bachelor’s degree.

Engineers and computer scientists entering the advanced technical workforce are witnessing rapid change in expectations of fluency in the fundamentals of Artificial Intelligence (AI) and Machine Learning (ML), and their application across virtually every discipline and industry.

Get ahead of this technological revolution with UWM’s Artificial Intelligence and Machine Learning master’s degree, our newest concentration, welcoming full- and part-time students from many different STEM-related backgrounds.

Financial incentives include a $2,000 guaranteed scholarship plus we’ll waive your application fee. No GRE is required. Up to $4,000 in merit-based scholarships per student available (see “Generous Financial Incentives” tab below).

Microsoft Chairman and CEO Satya Nadella (’80, MS CS), is among many successful innovators who chose UWM for their technology-related graduate studies. Microsoft chose the Connected Systems Institute to host the nation’s only manufacturing-focused AI Co-Innovation Lab. This lab serves as a hub, connecting manufacturers in Wisconsin and elsewhere with Microsoft’s artificial intelligence experts and developers.

Program Type

Master’s

Program Format

On Campus

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71% of business leaders say they’d rather hire a less experienced candidate with AI skills than a more experienced candidate without them.

2024 Work Trend Index Annual Report from Microsoft and LinkedIn

*McKinsey Digital; 1/28/25 Superagency in the workplace: Empowering people to unlock AI’s full potential.

AI & ML specialists#3fastest-growing jobs (World Economic Forum 2025)
W/in 6 mos. of graduation97%of students launch careers or continue education
In the next 3 years92%of companies plan to increase Gen AI investment.*

Artificial Intelligence and Machine Learning Masters developed to meet your needs

  • Convenient: With class times convenient for working professionals.
  • No GRE required. Your application fee is waived.
  • A limited number of merit scholarships are available; no separate application needed.
  • Not just for Computer Science or Engineering bachelor’s degree holders: We welcome applicants with a broad range of prior degrees, including not only computer science and engineering, but science, economics, finance, psychology or any other area that requires academic preparation in math and programming. Applicants with other undergraduate degrees will also be considered via holistic assessment of their academic record and professional experience.
  • Flexible. Builds upon 15-credit Artificial Intelligence and Machine Learning Certificate, enabling you to expand your learning to a include a wide array of topics that interest you, regardless of your interests.
  • 30-credit thesis or 31-credit non-thesis option.

Who should apply?

Anyone interested in advancing or changing their career with in-demand skills in this fast-growing field. You’ll learn to apply artificial intelligence techniques to many engineering domains.

We welcome students with a background in many STEM and STEM-adjacent disciplines, including science, technology, engineering, math, data science, and social sciences, such as psychology or geography, to name a few. If you have a bachelor’s degree in a STEM or STEM-adjacent field, you could be eligible to enroll.

AI & ML masters program provides skills employers seek

  • Accelerate data-driven decision-making and innovation.
  • Gain interdisciplinary skills, enabling you to address complex problems from different perspectives.
  • Tackle real-world problem-solving, assuring you are a valuable contributor to innovation in research or industry.
  • Drive innovation across multiple industries, including healthcare, manufacturing, climate modeling, natural language processing, embedded electronic systems, data science, and connected systems, such as the internet of things, to name a few.
  • Demonstrate your adaptability to the workforce of the future. Advances in Artificial Intelligence and Machine Learning require a versatile and trained workforce; earning this degree proves your readiness to take on these challenge.
  • Develop expertise on ethical considerations. You’ll learn the limits of using Artificial Intelligence and Machine Learning and how to determine and responsible solutions to issues.
  • Industry advisory feedback–our coursework is relevant to current and future demands.

Part-time and full-time options:

In-person, evening and some online courses available to address all student types.

Estimated time to completion:

  • Full time: 3 semesters
  • Part time: 5 semesters

Two options

  • 30-credit thesis
  • 31-credit non-thesis

Generous financial support is available for students enrolling in this program through Fall 2026:

  • GRE waived
  • Application fee waived ($75 savings)
  • $2,000 guaranteed scholarship to all students who enroll in the program with 12 or more credits, in-person or online (available starting in Spring 2026), earned from the College of Engineering & Applied Science each year
  • Up to $4,000 in additional merit-based scholarships per two-year master’s degree, to students enrolled in the program with 16 or more credits, in-person or online (available starting in Spring 2026), from the College of Engineering & Applied Science each year

Computer Science Faculty

John Boyland
Boyland, John
  • Professor, Computer Science
Christine Cheng
Cheng, Christine
  • Associate Professor, Computer Science
Mahsa Dabagh
Dabagh, Mahsa
  • Assistant Professor, Biomedical Engineering
  • Affiliate Assistant Professor, Computer Science
Thomas Haigh
Haigh, Thomas
  • Professor, History - General
  • Affiliate Professor, Computer Science
Rohit Kate
Kate, Rohit
  • Associate Professor, Computer Science
Chiu Law
Law, Chiu
  • Associate Professor, Electrical Engineering
  • Associate Professor, Computer Science
Jake Luo
Luo, Jake
  • Associate Professor, Health Informatics & Administration
  • Affiliate Professor, Computer Science
  • Graduate Program Director, Health Care Informatics
Amol Mali
Mali, Amol
  • Associate Professor, Computer Science
faculty photo susan mcroy
McRoy, Susan
  • Professor, Computer Science
  • Department Chair, Computer Science
Ayesha Nipu
Nipu, Ayesha Siddika
  • Teaching Faculty II, Computer Science
Sadia Nowrin
Nowrin, Sadia
  • Teaching Faculty II, Computer Science
Shana Ponelis
Ponelis, Shana
  • Associate Professor, Information Studies Administration
  • Affiliate Professor, Computer Science
Mohammad Rahman
Rahman, Mohammad Habib
  • Richard and Joanne Grigg Professor, Mechanical Engineering
  • Department Chair, Mechanical Engineering
  • Affiliate Professor, Computer Science and Biomedical Engineering
  • Switzer Research Distinguished Fellow
Rock, Jayson
Rock, Jayson
  • Teaching Faculty 3, Computer Science
  • Web Development Certificate Coordinator
Bob Sorenson
Sorenson, Robert
  • Teaching Faculty 3, Computer Science
Jerald Thomas
Thomas, Jerald
  • Assistant Professor, Computer Science
faculty image weizhong wang
Wang, Weizhong
  • Associate Professor, Electrical Engineering
  • Associate Professor, Computer Science
faculty member zeyun Yu
Yu, Zeyun
  • Professor, Computer Science
  • Professor, Biomedical Engineering
  • Director, Big Data Analytics and Visualization Lab
Zhen Zeng
Zeng, Zhen
  • Assistant Professor, Computer Science
Jun Zhang
Zhang, Jun
  • Professor, Electrical Engineering
  • Professor, Computer Science
Tian Zhao
Zhao, Tian
  • Associate Professor, Computer Science

Electrical Engineering Faculty

Brian Armstrong
Armstrong, Brian
  • Professor, Mechanical Engineering
Rob Cuzner
Cuzner, Robert
  • Richard and Joanne Grigg Professor
  • Professor, Electrical Engineering and Computer Science
  • Director, Center for Sustainable Electrical Energy Systems (SEES)
  • Site Director, Center for GRid-Connected Power Electronic Systems (GRAPES)
George Hanson
Hanson, George
  • Professor Emerit, Electrical Engineering
faculty member yi-hu
Hu, Yi
  • Associate Professor, Electrical Engineering
  • Department Chair, Electrical Engineering
  • Associate Professor, Computer Science
Nikolai Kouklin
Kouklin, Nikolai
  • Professor, Materials Science and Engineering
Chiu Law
Law, Chiu
  • Associate Professor, Electrical Engineering
  • Associate Professor, Computer Science
Devendra Misra
Misra, Devendra
  • Professor Emerit, Biomedical Engineering
  • Professor Emerit, Electrical Engineering and Computer Science
Lingfeng Wang
Wang, Lingfeng
  • Richard and Joanne Grigg Faculty Fellowship
  • Professor, Electrical Engineering
  • Professor, Computer Science
faculty image weizhong wang
Wang, Weizhong
  • Associate Professor, Electrical Engineering
  • Associate Professor, Computer Science
Jun Zhang
Zhang, Jun
  • Professor, Electrical Engineering
  • Professor, Computer Science

Advising

Therese Crary
Crary, Therese
  • Advisor, Graduate Programs
  • Computer Science, Electrical Engineering, Biomedical Health Informatics
Bob Packard
Packard, Robert
  • Advisor, Graduate Programs
  • Civil/Environmental Engineering, Mechanical Engineering, Biomedical Engineering, Industrial/Manufacturing Engineering, Materials Science & Engineering
Academic Catalog
All Academic Resources
Important Dates
Applications are accepted on a rolling basis.
Accreditation
This program is accredited by the U.S. Higher Learning Commission (HLC).
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Contact
ceas-grad@uwm.edu

Street Address
College of Engineering & Applied Science
3200 North Cramer Street
Milwaukee, WI 53211

Mailing Address
College of Engineering & Applied Science
P.O. Box 784
Milwaukee, WI 53201-0784