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EPI 288 - Introduction to Data Mining and Risk Prediction or return to Course Catalog Search

190331 – Section 2   

SchoolDepartmentFaculty
Harvard T.H. Chan School of Public HealthEpidemiologyNancy Cook and Earl Cook
TermDay and Time
Spring (Full Term) 2018  (show academic calendar)Contact host school for schedule
Credits
2.5  (show credit conversion for other schools)
Credit Level
Graduate

Description
This course will present an introduction to the methods of data mining and predictive modeling, with applications to both genetic and clinical data. Basic concepts and philosophy of supervised and unsupervised data mining as well as appropriate applications will be discussed. Topics covered will include multiple comparisons adjustment, cluster analysis, principal component analysis, and predictive model building through logistic regression, classification and regression trees (CART), multivariate adaptive splines (MARS), neural networks, random forests, and bagging and boosting.Meeting Note: This is an online course with pre-recorded lectures and will not have specific meeting timesPrerequisite: EPI 522 or EPI 236 or BST 213 or permission of the instructorCourse Restricted to students in the MPH-EPI program or a summer-only degree program. Other students can enroll with instructor permission. Preference is given to students in the MPH-EPI program.

Prerequisite(s)
EPI 522 or EPI 236 or BST 213 or permission of the instructor Student must be in the MPH-EPI program or a summer-only degree program. Other students can enroll with permission of the instructor.

 
Cross Registration
Eligible for cross-registration
With permission of instructor/subject to availability

MIT students please cross register from MIT's Add/Drop application.

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