Decision Trees and Model Selection Course
Course Overview

In this course, you will be introduced to the classification and regression trees (CART) algorithm. By implementing CART, you will build decision trees for a supervised classification problem. Next, you will explore how the hyperparameters of an algorithm can be adjusted and what impact they have on the accuracy of a predictive model. Through this exploration, you will practice selecting an appropriate model for a problem and dataset. You will then load a live dataset, select a model, and train a classifier to make predictions on that data.

The courses Problem-Solving with Machine Learning, Estimating Probability Distributions, and

  • Learning with Linear Classifiers
  • are required to be completed prior to starting this course.

    Who should enroll in this course?
    • Programmers
    • Developers
    • Data analysts
    • Statisticians
    • Data scientists
    • Software engineers
    Machine Learning Certificate