INTRODUCTION Explainable AI, or XAI for short, is a more advanced domain within data science aimed at making AI and machine learning model decisions and forecasts understandable and interpretable to humans. While data science models have grown in their level of sophistication, especially with the use of deep learning and ensemble techniques, there is limited interpretability for how those models arrive at specific outcomes. XAI addresses this challenge by providing model behavior explanations that improve trust, accountability, and reliability in data-driven systems. XAI has mission-critical applications across sensitive domains such as healthcare, finance, law, and autonomous systems. Explainable AI, or XAI for short, is a more advanced domain within data science aimed at making AI and machine learning model decisions and forecasts understandable and interpretable to humans. While data science models have grown in their level of sophistication, especially with the use of deep le...