Course overview
This course introduces the concept of explainability in AI, empowering learners to interpret and communicate the reasoning behind AI-driven outcomes. Through practical tasks and real-world manufacturing scenarios, participants will gain hands-on experience applying XAI methods to AI projects.
What you will learn:
- How to assess explainability requirements in AI-driven applications.
- How to compare XAI methods based on model type and goal.
- How to map the right XAI tools to each system’s context.
- How to design explainable solutions for manufacturing use cases.
- How to evaluate fairness, bias, and transparency in AI systems.
Follow the ‘go to course’ and sign up!
