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This course provides students hands on experiences with data science and machine learning for biomedical engineering. Students will work with datasets to explore topics in biomedical data processing (convolution, denoising, filtering, edge detection, template matching), biomedical data reduction (feature extraction, principal component analysis), and biomedical data regression, classification (including deep learning), and clustering. Background: Signals and Systems, Calculus III, Linear Algebra, Probability and Statistics.