Understanding Explainable AI (XAI)

Explainable AI focuses on building machine learning models that provide transparent, human-understandable reasoning behind their predictions. You will explore techniques that make AI models more transparent and interpretable, such as SHAP, LIME, and counterfactual explanations. Mastering explainable AI is critical in regulated sectors like finance and healthcare, where understanding AI decisions is essential for compliance and trust. It’s a key differentiator for AI engineers, data scientists, and machine learning professionals aiming to build responsible AI systems.