At the Opus College of Engineering, we are world-class engineers who will lead bold, innovative change to serve the world in the Jesuit tradition.
ENGINEERING CERTIFICATE PROGRAMS
Attend Our Open House: November 19, 2024Join us for an Open House for our Engineering Programs. Open House events allow students to learn about programs in a large group, presentational-style setting. Attendees will also have the opportunity to break out into smaller groups and discuss programs and questions with faculty and current students in their fields. The Open House will be held on Tuesday, November 19, 2024 at 6pm CST. Please RSVP at the link below. We look forward to seeing you there! |
At the Opus College of Engineering, we are world-class engineers who will lead bold, innovative change to serve the world in the Jesuit tradition.
By completing the graduate certificate in machine learning for engineering applications, you'll develop the capabilities required to apply current tools and appropriate approaches to solve complex problems in a variety of domains. You’ll gain a greater technical understanding of the elements of machine learning, including algorithms, intelligent systems, neural networks, pattern recognition and deep learning.
We recognize the importance of flexibility to those pursuing graduate education, especially to practicing engineers. That’s why we offer you the opportunity to complete our certificates on a full- or part-time basis.
Credit Hours
Months to Complete*
Online and On-Campus
*12-18 months to complete, based on a student's individualized plan
Topic Areas
The flexible program includes one required course and three elective courses. The required course is designed to explore theoretical foundations of machine learning including:
The remaining credits come from a wide range of elective courses.
Additional Program Highlights
Flexible course of study
Students can achieve their professional goals with great autonomy by selecting courses that help them achieve their goals.
Industry focused
Program was designed in response to shifts in the labor market as the digital economy grows and creates the opportunity to provide the skills that future engineers will need.
Apply the in-depth coursework directly and immediately to your current position.
Study with expert faculty
Students work closely with ÏòÈÕ¿ûÊÓƵfaculty, who are experts with extensive industry experience and teach students how to become an "Ignatian Engineer" and develop a skill set with the technical expertise and a reflective mindset to recognize the impact on the world.   Meet the faculty>>
Learn from industry experts
Industry experts will participate in this certificate program through workshops and guest lectures, allowing students to learn and apply their skills based on their expertise.
View the Course Work
Total Credit Hours 12
Required Course:
Machine Learning
Elective Courses
Choose three from the following:
Other courses as approved by the Certificate Faculty Sponsor, the EECE director of graduate studies (DGS) and the chair of the EECE department.
Learning Outcomes
At the end of the certificate, you will be able to:
Apply Your Knowledge
By connecting class work to real-world engineering organizations, industry and academia can come together to embrace new ways of thinking and working together to tackle real problems and solutions.
Graduates of the program are likely to find positions in a wide range of organizations across industries, including:
Ready to learn more about Marquette's engineering machine learning certificate program? Reach out directly to our program recruiter or fill out the form below (all fields required) and we will respond to you shortly.
Tim Carter
phone: (414) 288-7139
email: tim.carter@marquette.edu
To be eligible for admission to the Graduate School at ÏòÈÕ¿ûÊÓƵ, applicants must meet the following requirements:
Applicants who do not have an engineering degree must complete prerequisite engineering requirements. The list of required prerequisite course(s) is determined during the academic advising process. Students who do not meet the 3.000 requirement, but have completed one year of engineering work experience, are reviewed and considered based upon a letter of recommendation from their supervisor to determine the applicant’s ability to complete advanced course work.
Read all application instructions prior to beginning an application.
1Upon admission, final official transcripts from all previously attended colleges/universities, with certified English translations if original language is not English, must be submitted to the Graduate School within the first five weeks of the term of admission or a hold preventing registration for future terms will be placed on the student’s record.
2Upon admission, an official course-by-course transcript/academic record evaluation must be submitted to the Graduate School within the first five weeks of the term of admission or a hold preventing registration for future terms will be placed on the student’s record.
This program has rolling admission, which means you may apply and submit all application materials any time before the following dates:
Applicants who wish to be considered for merit-based financial aid (scholarships) should be aware of the merit-based financial aid deadlines by which all applicant materials must be received by the Graduate School:
Dr. Richard J. Povinelli (PhD, ÏòÈÕ¿ûÊÓƵ) is an associate professor in the department of Electrical and Computer Engineering and has over 100 publications in the areas of machine learning and signal processing. He has 25 years of academic and seven years of industrial experience. Dr. Povinelli worked at General Electric Corporate Research and Development as a software engineer and at GE Medical Systems as a project manager.
Henry Medeiros (PhD, Purdue University) is an Assistant Professor of Electrical and Computer Engineering, and his research interests include computer vision, robotics, sensor networks, and embedded systems. Before joining Marquette, he was a Research Scientist at the School of Electrical and Computer Engineering at Purdue University and the Chief Technology Officer of Spensa Technologies, a high-tech start-up company located at the Purdue Research Park.
Dong Hye Ye (PhD, University of Pennsylvania) is an Assistant Professor of Electrical and Computer Engineering. His research interests include machine learning, medical image processing, CT reconstruction, metal artifact reduction, microscopic imaging, automatic target recognition, and unmanned aerial vehicles.