Back to Explainable Machine Learning (XAI)
Learner Reviews & Feedback for Explainable Machine Learning (XAI) by Duke University
14 ratings
About the Course
As Artificial Intelligence (AI) becomes integrated into high-risk domains like healthcare, finance, and criminal justice, it is critical that those
responsible for building these systems think outside the black box and develop systems that are not only accurate, but also transparent and
trustworthy. This course is a comprehensive, hands-on guide to Explainable Machine Learning (XAI), empowering you to develop AI solutions
that are aligned with responsible AI principles. Through discussions, case studies, programming labs, and real-world examples, you will gain the
following skills: 1. Implement local explainable techniques like LIME, SHAP, and ICE plots using Python. 2. Implement global e...
responsible for building these systems think outside the black box and develop systems that are not only accurate, but also transparent and
trustworthy. This course is a comprehensive, hands-on guide to Explainable Machine Learning (XAI), empowering you to develop AI solutions
that are aligned with responsible AI principles. Through discussions, case studies, programming labs, and real-world examples, you will gain the
following skills: 1. Implement local explainable techniques like LIME, SHAP, and ICE plots using Python. 2. Implement global e...
Top reviews
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1 - 3 of 3 Reviews for Explainable Machine Learning (XAI)
By Peter P
•Jan 17, 2025
If you are going to use AI in your organization, this course is essential.
By Paul R
•Feb 16, 2025
Great! I love how they showed the cuttting edge of research.
By Jorge A R U
•Feb 20, 2025
Nice review of existing methods. Nice labs. However, lecturer does not explain concepts, is just like reading a book.