This module focuses on the basics of decision trees—a type of model used to make predictions based on data. This model is one way AI models can be developed, and its development requires a solid grasp of several statistical concepts. Throughout this module, you will:

Explore the components of decision trees
Practice identifying them
Develop your own basic decision tree

By the end of this module, you’ll understand the basics of how a decision tree is constructed.

Learning Task	Outcome	Why It Matters in AI
Create a decision tree using yes/no splits that lead to meaningful conclusions.	SR.A.1a Represent data on a single count or measurement variable.	You’ll understand how AI breaks complex decisions into simple steps machines can use to make predictions. You’ll explore the process of organizing data to make an effective predictive model.

Vocabulary Term	Definition
Predictive Model	A predictive model is a statistical approach that analyzes data to identify patterns and relationships, which it applies to estimate unknown or future outcomes.
Decision Tree	A type of predictive model used to make predictions based on data. A basic decision tree model consists of asking a 'yes' or 'no' question, and then dividing the data based on the answer.
Nodes	The questions or distinct chunks of information. In addition to standard nodes, there are two specialized types of nodes; roots and leaves.
Root	The first question that starts the whole decision tree.
Leaves	The points in the decision tree where the information cannot be separated further.
Branches	The spots where information is divided based on the answer to a question.
Training Data	A set of examples used to teach AI models patterns and relationships, helping it make accurate predictions or decisions based on new data.
Labels	A label is the specific piece of information or outcome your AI model is built to predict or classify.
Artificial Intelligence	A computer program that can make choices based on information in its environment and complete tasks that normally require human intelligence.