What You’ll Learn
Define key Explainable AI terminology and their relationships to each other
Describe commonly used interpretable and explainable approaches and their trade-offs
Evaluate considerations for developing XAI systems, including XAI evaluation approach, robustness, privacy, and integration with decision-making
Skills You’ll Gain
Shareable Certificate
Earn a shareable certificate to add to your LinkedIn profile.
Develop Your Specialized Knowledge
Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate
There are 3 modules in this course
In this module, you will be introduced to the concept of Explainable AI and how to develop XAI systems. You will learn how to differentiate between interpretability, explainability, and transparency in the context of AI; how to identify algorithmic bias, and how to critically examine ethical considerations in the context of responsible AI. You will apply these learnings through discussions and a quiz assessment.
In this module, you will learn how to describe XAI techniques and approaches, examine the trade-offs and challenges in developing XAI systems, and understand emerging trends in applying XAI to Generative AI applications. You will apply these learnings through discussions and a quiz assessment.
In this module, you will learn how to integrate XAI explanations into decision-making processes, understand considerations for the evaluation of XAI systems, and identify ways to ensure robustness and privacy in XAI systems. You will apply these learnings through case studies, discussion, and a quiz assessment.