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Artificial Intelligence and Machine Learning
Graduate Certificate

Earning a Graduate Certificate in AI & Machine Learning from UWM’s College of Engineering & Applied Science is a smart way to accelerate your career—whether you’re a working professional looking to upskill or a graduate student planning to “stack” certificates on the path to a master’s degree.

With the global AI market growing at more than 40% annually*, every industry now needs talent with hands-on expertise in artificial intelligence, machine learning and data-driven decision-making. UWM’s program is shaped by industry advisory input, ensuring you learn the tools and techniques employers are actively seeking.

You’ll study at a university trusted by innovators—including Microsoft Chairman and CEO Satya Nadella, who completed graduate studies in computer science at UWM.

Ready to go deeper? UWM now offers a Master of Science in Artificial Intelligence & Machine Learning for those who want advanced, comprehensive training.

*Grand View Research

Program Type

Graduate Certificate

Program Format

On Campus

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Developed to meet your needs

  • Convenient: With attention to class times convenient for working professionals.
  • 15-credit program can be completed in one year.
  • No GRE required.
  • Not just for computer science degree holders: We welcome applicants with a broad range of undergraduate degrees, including science, engineering, computer science, economics, finance or any other area that requires academic preparation in math and programming. Applicants with other prior degrees will also be considered via holistic assessment of their academic record and professional experience.
  • Looking for deeper experience? New Master of Science in Artificial Intelligence and Machine Learning now offered. Learn more about this new program.
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Explore how our college is working with AI in Engineering and Computer Science

A 15-credit program that updates your skills

  • Six credits (two courses) will be in general areas to provide an understanding of the theory and practice of machine learning.
  • Another nine credits will be electives covering application areas of machine learning, such as natural language processing, computer vision, AI techniques and algorithms and software engineering for AI/ML.
  • View the Academic Catalog for specifics.

Computer Science Faculty

Boyland, John
  • Professor, Computer Science
Cheng, Christine
  • Associate Professor, Computer Science
Dabagh, Mahsa
  • Richard and Joanne Grigg Professorship
  • Associate Professor, Biomedical Engineering
  • Affiliate Associate Professor, Computer Science
Kate, Rohit
  • Associate Professor, Computer Science
Kouklin, Nikolai
  • Professor, Computer Science
Law, Chiu
  • Associate Professor, Electrical Engineering
  • Associate Professor, Computer Science
Luo, Jake
  • Associate Professor, Health Informatics & Administration
  • Affiliate Professor, Computer Science
  • Graduate Program Director, Health Care Informatics
Mali, Amol
  • Associate Professor, Computer Science
McRoy, Susan
  • Professor, Computer Science
  • Department Chair, Computer Science
Nipu, Ayesha Siddika
  • Teaching Faculty II, Computer Science
Nowrin, Sadia
  • Teaching Faculty II, Computer Science
Rahman, Mohammad Habib
  • Richard and Joanne Grigg Professorship
  • Professor and Department Chair, Mechanical Engineering
  • Affiliate Professor, Computer Science and Biomedical Engineering
  • Switzer Research Distinguished Fellow
Rock, Jayson
  • Teaching Faculty 3, Computer Science
  • Web Development Certificate Coordinator
Sorenson, Robert
  • Teaching Faculty 3, Computer Science
Thomas, Jerald
  • Assistant Professor, Computer Science
Wang, Weizhong
  • Associate Professor, Electrical Engineering
  • Associate Professor, Computer Science
Yu, Zeyun
  • Professor, Computer Science
  • Professor, Biomedical Engineering
  • Director, Big Data Analytics and Visualization Lab
Zeng, Zhen
  • Assistant Professor, Computer Science
Zhang, Jun
  • Professor, Electrical Engineering
  • Professor, Computer Science
Zhao, Tian
  • Associate Professor, Computer Science

Electrical Engineering Faculty

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

Advising

Crary, Therese
  • Advisor, Graduate Programs
  • Computer Science, Electrical Engineering, Biomedical Health Informatics
Packard, Robert
  • Advisor, Graduate Programs
  • Civil/Environmental Engineering, Mechanical Engineering, Biomedical Engineering, Industrial/Manufacturing Engineering, Materials Science & Engineering

Academic Catalog
Schedule of Classes
Take a Virtual Tour of Computer Science
Contact
Computer Science
Contact Info: ceas-cs@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
Electrical Engineering
Contact Info: ceas-ee@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