Ethics in Data Science is a practical guide to navigatie the moral challenges of modern data use, covering topics from ethical data collection and privacy to algorithmic bias and AI accountability. The book offers clear frameworks, real-world case studies, and regulatory insights. Each chapter includes learning outcomes, summaries, and assessments to reinforce the understanding of the readers. The book is designed for students, educators, and professionals. This book emphasizes transparency, fairness, and responsibility in every stage of the data lifecycle - whether it is with regard to building models or shaping policies - and helps to make ethical decisions in an increasingly data-driven world.

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