This book serves as an accessible yet in-depth introduction to this cutting-edge intersection, where quantum theory and machine learning unite to unlock new computational possibilities. This book is crafted for students, educators, researchers, and forward-looking professionals in STEM and business fields who wish to gain a foundational understanding of Quantum AI. It breaks down complex topics into digestible concepts, guiding readers through the fundamentals of quantum mechanics, the mechanics of intelligent systems, and the emerging field of quantum machine learning. While tremendous progress has been made individually in both quantum computing and AI, there remains a gap in accessible resources that explain their integration. This book fills that void by presenting a holistic overview of how quantum principles can elevate machine learning processesoffering insights into optimization, modeling, simulation, and data processing at scales previously unimaginable with classical methods.

Students gain a valuable interdisciplinary foundation in a rapidly growing area of computing, learning both the technical underpinnings and applied potential of Quantum AI. Educators appreciate the book's structured layout, engaging content, and classroom-ready elementssuch as illustrative examples, reflection prompts, and references for further studythat support both conceptual understanding and practical exploration.

Whether you're a learner preparing for the next wave of technological disruption or an instructor shaping tomorrow's innovators, quantum minds equips you with the tools to navigate and contribute to the evolution of intelligent, quantum-powered technologies.

Contains clear introduction to quantum information science and computation with exploration of quantum machine learning Serves as an accessible yet in-depth introduction to this cutting-edge intersection Breaks down complex topics into digestible concepts

Autorentext

Madhusudan Singh, Ph.D., SMIEEE, is an associate teaching professor and leads Blockchain Data Intelligence (Blockchain Innovation) Lab in the Department of Computer Science and Engineering at the College of Engineering at The Pennsylvania (Penn) State University, University Park, State College, PA, USA. He previously served as an associate professor and chair of Data Analytics in the Department of Entrepreneurship and led the Center for Blockchain Technology and Data Analytics at Long Island University, Brooklyn, New York. Before that, he was an assistant professor in the Business department and founder of the Quantum Computing Innovation Center at the Oregon Institute of Technology (OregonTech), USA; his previous roles include an assistant professor and led the Nexus Cybersecurity Research Center (Applied AI/Data Science & Blockchain Technology) at Woosong University in South Korea. Bharat S. Rawal is a full Professor and a department head of Computer Science and Digital Technologies Department at Grambling State University, USA, and a senior fellow at US, Navy. His research focuses on network security, cloud computing, and security, blockchain, Big Data, analytical modeling, smart grid, and next-generation cyber defense. He has published several peer-reviewed conference proceedings, and journal publications, and has two patents. He is a member of (ACM, IEEE, IET, etc.). He received his D.Sc. degree in IT from Towson University Maryland. Previous Faculty Positions: Full Professor Department Chair Capitol Technology University, Associate Professor at Gannon University, Pennsylvania State University, Duke University, Industry Served: Biochem Pharmaceutical Industries, Ltd. Bashundhara Pharmaceutical, Ltd. Coracias Advance Technologies, LLC. Roles he served in the industry: Chairman, President, CEO, and Director of Marketing. His research interests are in Quantum Computing, Post-Quantum Cryptography, Cyber Security, Artificial intelligence, etc.

Inhalt

Quantum Mechanics Primer for Non-Physicists.- Overview of Quantum Computing.- Quantum Computing Keys.- Quantum Circuits.- Executing Circuits on Real Devices.- Quantum Algorithms.- Applications for Quantum Computing.- Quantum Computing with Artificial Intelligence: Introduction.- Quantum Machine Learning: A Primer.- Quantum Enhancements for AI Models.- Optimization and Portfolio Management.- Risk Assessment and Fraud Detection.- Decision-making and Strategy Formulation.- Quantum Hardware Landscape.- Programming Quantum Computers.- Realizing Quantum AI Projects.- Getting Involved in Quantum Computing.- The Future of Quantum Computing.- Quantum AI Trends and Future Outlook.