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University of New Hampshire

HDS805 - Machine Learning in Healthcare

Course Description

This course covers the foundations of machine learning in healthcare systems including algorithms related to classification and regression prediction in supervised setting, clustering and dimension reduction in an unsupervised setting. Topics include data preprocessing and classification techniques such as logistic regression, support vector machines, KNN, Na'ive Bayes', ensemble methods such as random forests, boosted trees, XGBoost, dimension reduction techniques such as principal components analysis, t-distributed scholastic neighborhood embedding, ISOMAP, locally linear embedding, UMAP, multidimensional scaling.

Prerequisites:

HDS800 - Math and Statistics for HDS with a minimum grade of D-
AND
HDS801 - The U.S. Healthcare System with a minimum grade of D-
AND
HDS802 - Programming in Healthcare with a minimum grade of D-

Tuition & Fees

Varies

Continuing education course enrollment costs and fees vary depending on program criteria and student eligibility. For more information on continuing education course costs click here.

Location

Durham, NH

Credits

3.0 units

Course Sections

Spring 2024

Mar 25 to May 17
crn: 53712
Format:
Campus: Durham
Time: TBA
Professor(s): Esmaeil Bahalkeh
Live Seat Count: 10 available seats - (16 days ago)
Varies
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