Real world experience,
delivered directly to you.
delivered directly to you.
Real world experience,
delivered directly to you.
delivered directly to you.
Get the Best of MSOE, Online
MSOE’s online machine learning programs are designed to bring the best of our campus—the faculty, stellar curriculum, and trusted reputation—to wherever you live and work. If you live and work in the Milwaukee area, faculty members are always happy to connect with you in person.
Discover Your Next Step
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MSOE and You: Better Together
Earn your master’s or certificate in machine learning online with MSOE. Complete the form to get a program details sheet for the program of your choosing—Master of Science in Machine Learning or Graduate Certificate in Applied Machine Learning—delivered to your inbox.
MSOE Students Rise to the Challenge
Learn with—and from—your fellow students. You may not be meeting in person on campus, but you will network and connect with your cohort. Through synchronous courses and meaningful course projects, you will connect with professionals who are just as driven and eager to learn as you are.
Applied Machine Learning Certificate Students
The following information on our latest cohort can give you a good idea of the background of the students in the certificate program and the types of professionals you can expect to see in your future cohort.
Undergraduate Majors
- Computer Engineering
- Computer Science
- Electrical Engineering
- Software Engineering
- Economics, Finance
- Math
Graduate Degrees and Areas of Study
- M.S.
- Ph.D.
- Computer Science
- Electrical Engineering
- Computer Engineering
- Engineering Management
Job Titles
- Software Engineer/Developer
- Electrical Engineer
- Data Scientist
- Data Engineer
- Vice President
- Manager
- Firmware Engineer
- Systems Engineer
Professional Levels
- Senior Staff
- Senior Manager
- Vice President
- Senior Staff
- Senior Manager
- Vice President
“The best part of the program is that it is designed for a working professional. The synchronous format is great, but if something comes up and I miss a class, I know I can catch up by watching the recording. Professors also offer flexible office hours.”
Max M., Graduate Certificate in Applied Machine Learning ’22
Solve Real-World Problems
MSOE’s online machine learning programs are focused on applying machine learning and AI technologies to solve real-world problems. Projects throughout both programs are integral to helping you develop and implement machine learning solutions. These projects are also designed to allow you to apply your learning to the fields of work that matter to you the most.
Examples include:
- Creating regression models that predict the sale prices of real estate properties
- Engineering new features to improve machine learning model prediction performance
- Applying a pre-trained version of the You Only Look Once (YOLO) model to perform object detection and segmentation with deep neural networks
- Creating machine learning models to distinguish between electrocardiograms indicating healthy patients and those with heart disease
- Applying dimensionality reduction and clustering techniques to explore a large data set of emails
- Analyzing transaction records to identify seasonal patterns in the sales of the products and make suggestions on product inventory levels and in-store displays
Data Science: Spatial Distributions of Real Estate Sales
Create a dashboard for spatial distributions of real estate based on prices, types, sizes, and characteristics like number of bedrooms and bathrooms. You will be tasked with inferring geographic properties like income ranges and urban vs suburban vs rural locations.
Technologies used: Pandas, interactive visualization libraries like Bokeh and folium
Technologies used: Pandas, interactive visualization libraries like Bokeh and folium
Machine Learning: Decision Boundaries
Learn how machine learning models partition the feature space to perform classification. You will interpret and manipulate the equations using linear algebra.
Technologies used: supervised learning, linear algebra, Scikit-learn, Numpy
Technologies used: supervised learning, linear algebra, Scikit-learn, Numpy
Machine Learning: Detection of Heart Disease from ECGs
Create machine learning models to distinguish between electrocardiograms (ECGs) indicating healthy patients and those with heart disease. This project involves engineering variables that characterize the shapes of the ECG signals for input into a machine learning model.
Technologies used: Scikit-learn, support vector machines (SVMs), Random Forests
Technologies used: Scikit-learn, support vector machines (SVMs), Random Forests
Deep Learning: Japanese Character Recognition
Learn to develop deep learning models for recognizing hand-written Japanese characters. You will compare dense (DNN) and convolutional neural network (CNN) architectures and optimizers (SGD, ADAM, RMSprop).
Technologies used: Keras, Tensorflow, dense neural networks (DNNs), convolutional neural networks (CNNs)
Technologies used: Keras, Tensorflow, dense neural networks (DNNs), convolutional neural networks (CNNs)
At MSOE, We Practice What We Teach
MSOE faculty are experts in applying and consulting on machine learning models for a variety of industries, including software, advertising, audiology and more. Your professors work with and consult on machine learning and AI technologies, and they bring that experience and their expertise directly to you.
Get to know the online machine learning program faculty.
Program Director, Master of Science in Machine Learning
Eric Durant, Ph.D., MBA, P.E.
Dr. Eric Durant is a professor and director of the machine learning program at MSOE. He also served for 16 years as director of MSOE’s computer engineering program. Dr. Durant researches the use of real-time audio processing with a focus on hearing aids, artificial intelligence and deep learning. He also has researched genetic algorithms to efficiently fit audio processing parameters in hearing aids, robust perceptual rank inferencing, beamforming, convex optimization and spatialization. He works regularly with Starkey Hearing Technologies as a senior digital signal processing (DSP) research engineer II and was a visiting professor at NVIDIA.
Education and Licensure:
Areas of Expertise:
Deep Learning, Audio Processing, Beamforming, Genetic Algorithms, Convex Optimization, Hearing Aids
Education and Licensure:
- Professional Engineer, WI License 45011-6
- Executive M.B.A., Business, University of Wisconsin-Milwaukee
- Ph.D., Electrical Engineering, University of Michigan
- M.S.E., Electrical Engineering, University of Michigan
- B.S., Computer Engineering, Milwaukee School of Engineering
- B.S., Electrical Engineering, Milwaukee School of Engineering
Areas of Expertise:
Deep Learning, Audio Processing, Beamforming, Genetic Algorithms, Convex Optimization, Hearing Aids
Program Director, Graduate Certificate in Applied Machine Learning
RJ Nowling, Ph.D.
Dr. RJ Nowling is an assistant professor of computer science and director of the machine learning certificate at MSOE. In collaboration with students and external research groups, he applies machine learning and data science to genomic data with the goal of extracting interpretable knowledge.
Prior to joining MSOE, Dr. Nowling worked on applications of machine learning into web services at companies like Red Hat and AdRoll. He teachers courses in data science, machine learning and algorithms.
Education:
Areas of Expertise:
Computer Science, Machine Learning, Data Science, Genomics, Data Structures and Algorithms, Bioinformatics
Prior to joining MSOE, Dr. Nowling worked on applications of machine learning into web services at companies like Red Hat and AdRoll. He teachers courses in data science, machine learning and algorithms.
Education:
- Ph.D., Computer Science & Engineering, University of Notre Dame
- M.S., Computer Science & Engineering, University of Notre Dame
- B.S., Computer Science/Mathematics, Eckerd College
Areas of Expertise:
Computer Science, Machine Learning, Data Science, Genomics, Data Structures and Algorithms, Bioinformatics
Professor
Derek Riley, Ph.D.
Dr. Derek Riley is an expert in big data, artificial intelligence, computer modeling and simulation, and mobile computing/programming. He joined the MSOE faculty in 2016 and is a professor in the Electrical Engineering and Computer Science Department. He is also program director of MSOE’s Bachelor of Science in Computer Science program, which has a focus in artificial intelligence. In addition to teaching at MSOE, Riley provides consulting services and expert-witness services related to machine learning, deep learning, facial recognition, computational modeling, high-performance computing and other related fields. He is an NVIDIA DLI Certified Instructor.
Education:
Areas of Expertise:
Machine Learning, Deep Learning, Computational Science, Computer Science, Algorithms, High-Performance Computing, Scrum, Software Engineering
Education:
- Ph.D., Computer Science, Vanderbilt University
- M.S., Computer Science, Vanderbilt University
- B.S., Computer Science, Wartburg College
Areas of Expertise:
Machine Learning, Deep Learning, Computational Science, Computer Science, Algorithms, High-Performance Computing, Scrum, Software Engineering
Assistant Professor
Anthony van Groningen, Ph.D.
Dr. Anthony van Groningen joined the Mathematics Department faculty at MSOE in 2012. He teaches courses in discrete mathematics, engineering mathematics, calculus and vector analysis.
Education:
Areas of Expertise:
Lie Algebras and Representation Theory, Abstract Algebra, Mathematics Education
Education:
- Ph.D., Mathematics, University of Wisconsin-Milwaukee
- M.S., Mathematics, University of Wisconsin-Milwaukee
- B.S., Computer Science, Mathematics, University of Wisconsin-Milwaukee
Areas of Expertise:
Lie Algebras and Representation Theory, Abstract Algebra, Mathematics Education
Assistant Professor
Andrew McAninch, Ph.D.
Dr. Andrew McAninch is an assistant professor of philosophy in the Humanities, Social Science and Communication Department at MSOE. McAninch works in moral philosophy, broadly construed, and also has interests in areas of applied ethics, epistemology and philosophy of science. At MSOE, he teaches Ethics for Managers and Engineers, Bioethics and Philosophy of Mind and AI.
Education:
Areas of Expertise:
Political Philosophy, Ethics of Digital, Technologies and Artificial Intelligence, Bioethics, Moral Philosophy, Philosophy, Ethics, Applied Ethics, Epistemology, Engineering Ethics, Social Philosophy
Education:
- Ph.D., Philosophy, Indiana University Bloomington
- B.A., Philosophy and English, The University of Iowa
Areas of Expertise:
Political Philosophy, Ethics of Digital, Technologies and Artificial Intelligence, Bioethics, Moral Philosophy, Philosophy, Ethics, Applied Ethics, Epistemology, Engineering Ethics, Social Philosophy
Assistant Professor
John Bukowy, Ph.D.
Dr. John Bukowy is an assistant professor in MSOE's Electrical Engineering and Computer Science Department where he teaches courses in computer science, software development and machine learning. He joined the faculty in 2019. Before joining academia, he worked as a lead quality assurance engineer for MERGE Healthcare.
Education:
Areas of Expertise:
Software Development, Machine Learning
Education:
- Ph.D., Physiology, Medical College of Wisconsin
- M.S., Electrical Engineering, Illinois Institute of Technology
- B.S., Biomedical Engineering, Marquette University
Areas of Expertise:
Software Development, Machine Learning
Josiah Yoder, Ph.D.
Dr. Josiah Yoder is an associate professor in the Electrical Engineering and Computer Science Department at MSOE. He has a passion for teaching and undergraduate research, and his research interests include computer vision, deep learning and non-linear tracking.
Education:
Areas of Expertise:
Computer Vision, Deep Learning, Nonlinear Tracking, Artificial Intelligence
Education:
- Ph.D., Computer Engineering, Purdue University
- B.S., Computer Engineering, Rose-Hulman Institute of Technology
Areas of Expertise:
Computer Vision, Deep Learning, Nonlinear Tracking, Artificial Intelligence
Admissions Requirements
Learn more about the admissions requirements and process to upskill your career with machine learning expertise.
Master's in Machine Learning
Develop advanced skills to create and deploy machine learning solutions in your technical field with MSOE’s master’s in machine learning and artificial intelligence.
Machine Learning Graduate Certificate
Explore a focused and efficient pathway to building skills around machine learning and AI concepts that can be applied to your current work and to growing a successful career.
Machine learning is taking off globally. Join in and grow your career.
This is an exciting time to build a career working with machine learning and AI technologies. Get the skills you need to lead in this rapidly growing area of technology with MSOE.
Admissions Dates and Deadlines
Jan
17
Application Deadline
January 17
Spring 2025
Jan
21
Start Date
January 21
Spring 2025