Konstantinos V. Katsikopoulos – författare

Data science is transforming every aspect of modern life, from healthcare and urban planning to finance and governance. This comprehensive book provides an accessible yet rigorous exploration of the principles, methodologies, and applications of data science. It introduces readers to the evolution of data science, the role of artificial intelligence, and the philosophical foundations underpinning data‑driven discovery. By bridging theory and practice, this book provides a unique perspective on how data can be harnessed to solve complex, real‑world problems.Unlike other texts, this book integrates technical foundations with ethical, regulatory, and societal considerations. It covers the entire data science lifecycle, from acquisition and processing to advanced analytics, application development, and decision support. Real‑world case studies—including a detailed example of using electronic health records in Rwanda—illustrate how data science can drive impact in low‑ and high‑resource settings alike.Key Features:Comprehensive coverage of data science fundamentals, machine learning, and advanced analyticsIn‑depth exploration of ethical, governance, and regulatory challengesPractical insights into developing applications and decision support systemsGlobal case studies demonstrating applied data science in healthcare and public policyClear explanations suitable for multidisciplinary audiencesThis book is ideal for students, researchers, and professionals in data science, healthcare, public policy, and technology development. It equips readers with both the technical and ethical tools needed to navigate today’s data‑rich world and to leverage data for innovation, problem‑solving, and societal good.

Data science is transforming every aspect of modern life, from healthcare and urban planning to finance and governance. This comprehensive book provides an accessible yet rigorous exploration of the principles, methodologies, and applications of data science. It introduces readers to the evolution of data science, the role of artificial intelligence, and the philosophical foundations underpinning data‑driven discovery. By bridging theory and practice, this book provides a unique perspective on how data can be harnessed to solve complex, real‑world problems.Unlike other texts, this book integrates technical foundations with ethical, regulatory, and societal considerations. It covers the entire data science lifecycle, from acquisition and processing to advanced analytics, application development, and decision support. Real‑world case studies—including a detailed example of using electronic health records in Rwanda—illustrate how data science can drive impact in low‑ and high‑resource settings alike.Key Features:Comprehensive coverage of data science fundamentals, machine learning, and advanced analyticsIn‑depth exploration of ethical, governance, and regulatory challengesPractical insights into developing applications and decision support systemsGlobal case studies demonstrating applied data science in healthcare and public policyClear explanations suitable for multidisciplinary audiencesThis book is ideal for students, researchers, and professionals in data science, healthcare, public policy, and technology development. It equips readers with both the technical and ethical tools needed to navigate today’s data‑rich world and to leverage data for innovation, problem‑solving, and societal good.

This book examines how people make decisions under risk and uncertainty in operational settings and opens the black box by specifying the cognitive processes that lead to human behavior. Drawing on economics, psychology and artificial intelligence, the book provides an innovative perspective on behavioral operations. It shows how to build optimization as well as heuristic models for describing human behavior and how to compare such models on various dimensions such as predictive power and transparency, as well as discussing interventions for improving human behavior. This book will be particularly valuable to academics and practitioners who seek to select a modeling approach that suits the operational decision at hand.