This is a one-day course providing a hands-on introduction to machine learning techniques using R. The course is run by the Melbourne School of Population and Global Health in collaboration with the Dalla Lana School of Public Health (University of Toronto), and is designed for a multi-disciplinary audience including analysts, clinicians, researchers, students and others with an interest in applying machine learning techniques to health data. Topics covered include classification techniques, clustering, decision trees and neural networks, applied in a health context.
This course will consist of lectures and hands-on exercises using R software. Participants will be expected to bring a laptop computer with R pre-installed and should have a working knowledge of R programming. An optional R workshop will be offered prior to the course to provide participants with the programming skills required.
All participants will be expected to have a basic knowledge of epidemiological concepts. If you wish to discuss your suitability for this course, please contact HDAfirstname.lastname@example.org.
The next course will be held on 8th November 2019.
The course will be held at Graduate House, 220 Leicester Street, Carlton. Registration is at 8:45am for a 9:00 start with the formal program finishing at 4:30pm.
The introductory R workshop will be held from 1-5pm on 7th November 2019 at Graduate House.