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The “Learning XAI: Explainable Artificial Intelligence” course is designed to introduce learners to the essential concepts, tools, and techniques of XAI—an emerging field that aims to make AI systems more transparent, interpretable, and trustworthy. Targeted at data scientists, AI developers, business analysts, and decision-makers, the course addresses the growing need for AI models that are not only accurate but also understandable to humans. Participants will explore why explainability matters, particularly in high-stakes domains like healthcare, finance, and legal systems where...
Introduction
1. Explainable AI (XAI)
2. Humans and Machines Have Different Strengths and Weaknesses
3. The Case for Human Machine Collaboration
4. Examples of Possible XAI Applications
5. Next Steps
Conclusion
Walt Ritscher
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