What you will learn

• Identify common sources of bias in AI systems and apply tools to assess and mitigate them.

• Implement explainability methods, such as SHAP and LIME, to interpret and effectively communicate model behavior.

• Develop a responsible AI checklist aligned with transparency and fairness principles and apply it to AI projects to ensure ethical compliance.

• Evaluate AI projects for potential ethical risks and ensure alignment with compliance frameworks, such as the NIST AI RMF.