Decision Tree Classifier for Beginners in R
Welcome to this project-based course Decision Tree Classifier for Beginners in R. This is a hands-on project that introduces beginners to the world of statistical modeling. In this project, you will learn how to build decision tree models using the tree and rpart libraries in R. We will start this hands-on project by importing the Sonar data into R and exploring the dataset. By the end of this 2-hour long project, you will understand the basic intuition behind the decision tree algorithm and how it works.
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- Level Beginner
- Duration 3 hours
- Course by Coursera Project Network
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Offered by
Modules
Your Learning Journey
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Readings
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Plugin
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Lab
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Assignment
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Assignment
- Assess Your Knowledge
1
Labs
- Decision Tree Classifier for Beginners in R
3
Readings
- Project Overview
- Decision Tree Classifier for Beginners in R Script and data sets
- Additional Reading: Link to read about important concepts
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Dive into the world of statistical modeling with "Decision Tree Classifier for Beginners in R," a hands-on course designed for those new to data science. Led by a Coursera expert, this 2-hour project guides you through building decision tree models using R's tree and rpart libraries. Ideal for beginners with basic R knowledge, you'll learn to import data, partition datasets, and evaluate model performance using key metrics. Join now to enhance your data science skills with practical, project-based learning!
Arimoro Olayinka Imisioluwa