Introduction: Data Science is an interdisciplinary field that uses scientific methods, statistical techniques, algorithms, and computer systems to extract meaningful insights from structured and unstructured data. With the rapid advancement of digital technology, organizations today generate massive amounts of data through websites, mobile applications, sensors, business transactions, and social media platforms. This data contains valuable information that can support effective decision making. In traditional organizations, decision making was mostly based on human intuition, experience, or limited historical records. However, such decisions were often subjective and sometimes inaccurate. Data science provides a more reliable and evidence-based approach to decision making by analyzing large datasets and identifying hidden patterns or relationships. The field of data science combines several disciplines including statistics, machine learning, data mining, big data analytics, and data vi...
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...