6.03 Introduction to EECS via Medical Technology
Explores biomedical signals generated from electrocardiograms, glucose detectors or ultrasound images, and magnetic resonance images. Topics include physical characterization and modeling of systems in the time and frequency domains; analog and digital signals and noise; basic machine learning including decision trees, clustering, and classification; and introductory machine vision. Labs designed to strengthen background in signal processing and machine learning. Students design and run structured experiments, and develop and test procedures through further experimentation.
Lecture occurs 2:00 PM to 3:00 PM on Mondays and Wednesdays in 34-101.
This class counts for a total of 12 credits.
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