Quantum Learning : Bridging Artificial Intelligence, Quantum Computing, and Data Science in Education

Quantum Learning: Bridging Artificial Intelligence, Quantum Computing, and Data Science in Education explores the transformative intersection of three revolutionary technologies reshaping the future of learning. The concept of quantum learning provides a paradigm where quantum principles redefine machine learning models, enhance computational speed, and enable novel personalized education systems.

The book integrates artificial intelligence (AI), quantum algorithms, and data-driven pedagogy to reimagine classrooms and cognitive processes. Readers will discover how quantum-inspired neural networks, quantum data analysis, and intelligent tutoring systems can revolutionize educational delivery. Through interdisciplinary research, the work translates complex quantum and AI concepts into practical educational applications, featuring case studies and real-world insights that demonstrate how quantum-enhanced intelligence can personalize learning and improve outcomes. The text covers both theoretical frameworks and practical implementation strategies, offering a blueprint for adaptive, scalable learning ecosystems.

This wide-ranging book will appeal to a diverse audience of researchers, educators, technologists, and policymakers seeking to understand and shape the next generation of education innovation. By combining these domains into one book and using an accessible approach, it makes cutting-edge concepts comprehensible to both technical and non-technical readers, positioning it as an essential resource for anyone involved in educational technology, artificial intelligence research, or quantum computing applications in learning environments.

Pawan Whig, a leading expert in artificial intelligence and machine learning, is dedicated to advancing sustainable development. Dr. Whig's groundbreaking research and publications inspire innovative solutions for a greener, more equitable future.

Pavika Sharma is a distinguished researcher in artificial intelligence and machine learning, focusing on sustainable development. Her innovative work explores the intersection of technology and environmental conservation, driving progress towards a sustainable future.

Ahmad A. Elngar is an associate professor and Head of the Computer Science Department at Beni-Suef University. His research focuses on artificial intelligence, machine learning, and data science, with a strong emphasis on developing innovative computational models for education and intelligent systems.

Nuno Silva is the Chief Scientific and Technology Officer at UnifAI Technology, leading innovation at the intersection of artificial intelligence, quantum computing, and data science. His work focuses on advancing intelligent systems that enhance learning, decision-making, and sustainable technological transformation.