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Intermediate R, Machine Learning's four-class overview of machine learning using R statistical programming

Intermediate R: Machine Learning


This four week course introduces machine learning methods in R, specifically for analyses relevant to biomedical researchers. This course assumes attendees are familiar with basic R syntax, using packages, and basic data manipulation using tidyverse. The materials also assume a strong foundation in basic statistics as well as prior/concurrent participation in the course Concepts in Machine Learning (or equivalent experience). At the end of this course, you will be able to apply basic principles of machine learning to research questions and will have established a foundation for further exploration of machine learning techniques. Please see each set of class materials for specific learning objectives. These materials are developed by, the data and computational analysis training program at Fred Hutch. Each class in this course includes brief tutorials interspersed with challenge exercises.

Sessions of the course are periodically taught by instructors at Fred Hutch; each of the four classes is scheduled for two hours. The HackMD (interactive page used for sharing links and information) for instructor-led courses is here. The materials are also freely available for self-guided, work-at-your-own-pace study.

Required software: Software requirements for this course include:

The links above reference relevant sections of’s Software page.

Class materials

Materials for all lessons in this course include:

Solutions for exercises can be found in solutions.

For curriculum contributors and instructors

Please see the following resources for more information on: