Introduction to Decision Trees

Learn about the building blocks of decision trees, including entropy and information gain.


  • Learn the basics of decision trees
  • Learn the importance of entropy and information gain.

Mission Outline

1. Introduction
2. Overview of the Data Set
3. Converting Categorical Variables
4. Splitting Data
5. Creating Splits
6. Decision Trees as Flows of Data
7. Splitting Data to Make Predictions
8. Overview of Data Set Entropy
9. Overview of Data Set Entropy
10. Information Gain
11. Information Gain
12. Finding the Best Split
13. Build the Whole Tree
14. Next Steps
15. Takeaways

Course Info:

Decision Trees


The average completion time for this course is 10-hours.

This course requires a premium subscription. This course has four paid missions and one guided project.  It is the 22nd course in the Data Scientist in Python path.


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