EPI 288 - Introduction to Data Mining and Risk Prediction or return to Course Catalog Search
190331 – Section 2
|Harvard T.H. Chan School of Public Health||Epidemiology||Nancy Cook and Earl Cook|
|Term||Day and Time|
|Spring (Full Term) 2018 (show academic calendar)||Contact host school for schedule|
2.5 (show credit conversion for other schools)
Credit in Harvard T.H. Chan School of Public Health is equivalent to:
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.
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.
|Eligible for cross-registration|
With permission of instructor/subject to availability
MIT students please cross register from MIT's Add/Drop application.