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Supervised Machine Learning in R

Updated 05/2026
Generate, explore, evaluate, and tune the parameters of different supervised machine learning models.
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RMachine Learning25 hr3,029

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Track Description

Supervised Machine Learning in R

Supervised learning methods are central to your journey in data science. Learn how to generate, explore, and evaluate machine learning models by leveraging the tools in the Tidyverse. You'll learn about multiple and logistic regression techniques, tree-based models, and support vector machines. Finally, you'll learn how to tune your model's parameters for better performance.

Prerequisites

There are no prerequisites for this track

  • Course

    1

    Machine Learning in the Tidyverse

    Leverage tidyr and purrr packages in the tidyverse to generate, explore, and evaluate machine learning models.

  • Project

    bonus

    Assessing the Effectiveness of Medical Treatments

    Use logistic regression to determine which treatment procedure is more effective for kidney stone removal.

Supervised Machine Learning in R
6 Courses
Track
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FAQs

Is this Track suitable for beginners?

Yes, this track is suitable for beginners. It is designed to help students gain domain-specific expertise in supervised machine learning and will teach the tools in the Tidyverse, regression techniques, tree-based models, and support vector machines. Hyperparameter tuning and model parameter tuning will also be covered.

What is the programming language of this Track?

This track uses the R programming language.

Which jobs will benefit from this Track?

This track is particularly beneficial to data scientists, machine learning engineers, and researchers, though any job that requires knowledge of supervised machine learning will benefit from this track.

How will this Track prepare me for my career?

This track will provide students with a comprehensive overview of supervised machine learning methods and processes. With this knowledge, students will be better prepared to work as a data scientist in their field of choice.

How long does it take to complete this Track?

This track typically takes 25 hours to complete.

What's the difference between a skill track and a career track?

A skill track focuses on teaching individual concepts and skills, while a career track focuses on helping students to develop the skills and competencies they need for a particular career path.

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