Shaping the Digital Future: From Algorithms to Intelligence

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DOI:

https://doi.org/10.48001/978-81-980647-6-9

Abstract

In an era of rapid digital transformation, understanding the fundamental principles of computing is essential for navigating and shaping the future of technology. Shaping the Digital Future: From Algorithms to Intelligence offers a comprehensive exploration of computer science fundamentals alongside emerging innovations, bridging core theoretical concepts with real-world applications. This book begins by establishing a strong foundation in algorithms, data structures, and theoretical computing, providing readers with essential computational knowledge. It then delves into cutting-edge advancements in artificial intelligence, machine learning, and their transformative impact on industries. Further, it examines interconnected digital ecosystems, including the Internet of Things (IoT), big data, cloud computing, and cybersecurity—key drivers of modern technological infrastructure. Looking ahead, the book explores quantum computing, sustainable computing practices, and the societal implications of digital innovation.Beyond technical insights, this book emphasizes ethical and human-centric computing, addressing critical issues such as security, privacy, environmental sustainability, and the digital divide. By fostering responsible innovation and critical thinking, it encourages readers to not only understand technological progress but also contribute to its ethical and sustainable development. With a balanced combination of theoretical knowledge, practical applications, and future-focused insights, Shaping the Digital Future: From Algorithms to Intelligence serves as an essential resource for students, researchers, and professionals seeking to engage with the evolving digital landscape and drive meaningful technological advancements.

     

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Published

2025-03-17

How to Cite

Revathy, N., & Pandikumar, S. (2025). Shaping the Digital Future: From Algorithms to Intelligence. QTanalytics Publication (Books), 1–100. https://doi.org/10.48001/978-81-980647-6-9

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