This interdisciplinary opportunity with Opus College of Engineering will provide engineers the skills to participate on and lead cross-functional teams for their companies. If a Supply Chain Management student chooses to earn the certificate, admission to the Machine Learning certificate program must be obtained at the same time as admission to the Supply Chain Management program and will be enrolled simultaneously into both programs. Only credits taken while admitted to the certificate program may apply toward the certificate requirement.
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.
The 12 credits of course work is completed while enrolled in the MS-SC degree. The other 18 credits will be completed with Supply Chain courses; all of which are offered in an online environment.
Total Credit Hours 12
Choose three from the following:
- Visual Analytics
- Data Mining
- Ethical and Social Implications of Data
- Advanced Machine Learning
- Data at Scale
- Introduction to Algorithms
- Developments in Computer Software
Fundamentals of Artificial Intelligence
- Introduction to Intelligent Systems
- Introduction to Neural Networks and Fuzzy Systems
- Evolutionary Computation
- Algorithm Analysis and Applications
- Artificial Intelligence
- Pattern Recognition
- Neural Networks and Neural Computing
- Advanced Topics in Electrical and Computer Engineering
Other courses as approved by the Certificate Faculty Sponsor, the EECE director of graduate studies and the chair of the EECE department.