Machine Learning for Embedded Systems Graduate Certificate at George Mason University

Programme overview

Machine learning is a transformative force in technology, particularly in its application within embedded systems. These systems are specialized computer systems designed for specific tasks. Integrating machine learning into these systems, such as those found in self-driving cars, medical devices, and smart appliances, presents unique challenges.

Faculty: College of Engineering and Computing | Department: Department of Electrical and Computer Engineering | Duration: 12 credits | Study mode: full-time | Location: Fairfax, VA, United States

What you will study

Total 12 credits. Curriculum courses listed include Learning From Data; Machine Learning for Embedded Systems; Neuromorphic Computing; Big Data Technologies; Distributed and Federated Learning; Hardware Accelerators for Machine Learning.

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Application information

Entry requirements

The graduate certificate is open to all students who hold baccalaureate degrees in scientific and engineering disciplines from accredited universities in accordance with Graduate Admission Requirements . Non-degree graduate students are welcome to apply. Current degree seeking students in the College of Engineering and Computing may request admission as a secondary certificate .

Duration: 12 credits

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