Explainability in Artificial Intelligence Systems Learning Path Summative Assessment

Type of course:

Digital learning, Lesson

Language:

Duration:

20 minutes

Workload:

2 hours

Proficiency:

Intermediate

Target:

Professionals

This assessment evaluates the knowledge and understanding acquired throughout the Learning Path “Explainability in Artificial Intelligence Systems.” It scrutinizes the information, concepts, and skills absorbed during the course, aiming to assess the student’s proficiency in the subject matter and their ability to recognize it in manufacturing scenarios.

Learning outcomes

The student will understand the concepts of explainability, interpretability, and transparency in AI and recognize their importance in various applications, including manufacturing.
The student will explore practical methods and strategies for achieving AI explainability, mitigating bias, ensuring fairness, and enhancing transparency in manufacturing contexts.
The student will recognize the evolving trends and benefits of adopting Explainable AI in manufacturing and understand the importance of staying informed and competitive in the field.