Explainability techniques in Artificial Intelligence task

Type of course:

Digital learning, Lesson

Language:

Duration:

20 minutes

Workload:

2 hours

Proficiency:

Intermediate

Target:

Professionals

This “Explainability techniques in Artificial Intelligence Task” nugget focuses on offering a practical experiment with data from a real manufacturing company. The student is expected to apply their knowledge on how to implement simple, yet powerful techniques to fully explore the transparent nature of Interpretable AI models in a real-life business. Formative assessment is presented in the end to support the student’s comprehension of the materials.

Learning outcomes

The student will generate a graphical representation of a decision tree
The student will understand how to visually interpret a decision tree.
The student will extract and interpret coefficients and the independent term from a linear regression model