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!