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Springer Practical AI: A Blueprint for Building Intelligent Products

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Description

This book provides a comprehensive yet accessible introduction to the foundations, applications, and limitations of Artificial Intelligence, with a strong emphasis on practical relevance across industries. Designed for students without a technical background, the book explains the principles of data-driven models, classical machine learning, and modern generative AI, while addressing ethical, legal, and societal questions. The book walks through the full lifecycle of an AI product: from the foundational differences between AI, machine learning, and deep learning, through data quality and governance, model validation, and the operational realities of moving a prototype into production. Beyond the technical groundwork, Practical AI also tackles the questions that determine whether an AI initiative survives contact with the real world: how to structure a project using a dedicated AI Project Canvas, which roles and competencies a team actually needs, how to weigh cloud versus on-premises infrastructure and estimate real costs, and how to navigate an increasingly complex regulatory landscape, including the EU AI Act and region-specific data protection rules. A dedicated chapter on generative AI and large language models brings the book fully up to date, covering prompting principles, AI-assisted coding, and the opportunities and risks of working with these tools. Every chapter closes with exercises and worked solutions, and a capstone project chapter guides readers through producing a final report and pitch: making this as much a hands-on course companion as a reference for self-study. Whether used as a semester-long textbook or read cover to cover by a working professional, Practical AI offers a clear, no-code roadmap for anyone who needs to plan, manage, or evaluate an AI project with confidence.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
11 January 2027
Listed Since
15 July 2026

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