Master Decision Trees in R: Build, Predict & Evaluate
$49
ENROLL NOWCourse Overview
What You'll Learn
- By the end of this course, learners will build, interpret, and evaluate decision tree models in R for both classification and regression tasks.
- They will gain hands-on skills in data preprocessing, feature engineering, and model training, while applying predictive techniques to real-world datasets including advertisements, diabetes outcomes, Caeseats sales, and bank loan defaults.
- Through step-by-step coding practices, learners will implement decision tree algorithms using R packages like rpart and tree, visualize results, and evaluate performance with tools such as the confusion matrix.
By the end of this course, learners will build, interpret, and evaluate decision tree models in R for both classification and regression tasks. They will gain hands-on skills in data preprocessing, feature engineering, and model training, while applying predictive techniques to real-world datasets including advertisements, diabetes outcomes, Caeseats sales, and bank loan defaults. Through step-by-step coding practices, learners will implement decision tree algorithms using R packages like rpart and tree, visualize results, and evaluate performance with tools such as the confusion matrix. They will also learn to generate actionable insights for decision-making, with a particular emphasis on financial risk management applications. This course is uniquely designed to bridge theory with practice, combining structured progression for beginners with advanced applications for intermediate learners. By completing it, participants will not only master supervised learning with decision trees but also confidently apply their models to real-world business and financial scenarios, strengthening both their machine learning expertise and analytical decision-making skills.
Course FAQs
Is this an accredited online course?
Accreditation for 'Master Decision Trees in R: Build, Predict & Evaluate' is determined by the provider, EDUCBA. For online college courses or degree programs, we strongly recommend you verify the accreditation status directly on the provider's website to ensure it meets your requirements.
Can this course be used for continuing education credits?
Many of the courses listed on our platform are suitable for professional continuing education. However, acceptance for credit varies by state and licensing board. Please confirm with your board and {course.provider} that this specific course qualifies.
How do I enroll in this online school program?
To enroll, click the 'ENROLL NOW' button on this page. You will be taken to the official page for 'Master Decision Trees in R: Build, Predict & Evaluate' on the EDUCBA online class platform, where you can complete your registration.
