The ML course of Johns Hopkins University's popular Data Science Specialization on Coursera, taught in R. It centres on the caret package and walks through the model-building workflow — creating features, training, and evaluating models. Good if you are on the JHU R-based data-science track; less ideal if you want Python or a standalone ML course.
Good for: ML within the R-based Johns Hopkins Data Science track.
Less suitable if: You want Python, or you are not doing the JHU specialization.
Requirements: R and the earlier JHU Data Science courses help.
Realistic time: Around 15–20 hours over a few weeks.
About this course
Practical Machine Learning is the ML course in Johns Hopkins University's popular Data Science Specialization. Taught in R, it centres on the caret package and walks through the model-building workflow — creating training and test sets, preprocessing, fitting a spread of methods (trees, random forests, boosting), and evaluating them.
What you'll learn
Build predictive models in R with the caret package
Create and use training and test sets
Preprocess data and engineer features
Fit trees, random forests, and boosting models
Evaluate models and avoid overfitting
Apply a practical model-building workflow
This course includes
Yes
Certificate
Yes
Mobile access
English
Language
What it costs
You can audit the course free on Coursera. A certificate needs a Coursera subscription (about $49/month) or Coursera Plus, with financial aid available. It is part of the Johns Hopkins Data Science Specialisation.
Comparison · LBS
Compare alternatives for Practical Machine Learning
Same topic, different options. We surface the trade-offs others hide so you can pick the course that actually fits your time, budget, and goals.
A Johns Hopkins University certificate on Coursera is a credible learning record. It is a course certificate rather than a professional qualification or degree.
Last updated
Taught in R with the caret package. If your goal is Python-based ML, a Python course will fit better.
Instructor
JL
Jeff Leek
Coursera instructor
Created by Johns Hopkins biostatistics professors Jeff Leek, Roger Peng, and Brian Caffo, whose Data Science Specialization is one of the most-taken on Coursera. The approach is hands-on and R-centric.