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<p>This book presents a dual perspective on modern research and praxis on Data Science, Analytics, and AI/Machine Learning (DSA-AI/ML) system with small or big data. Consequently, potential readers—academics, researchers and practitioners interested in the systematic development and implementation of DSA-AI/ML systems—can be benefited with the high-quality conceptual and empirical research chapters focused on:</p><ul><li>Foundations, &#xa0;Development &#xa0;Platforms, and Tools on Engineering and Management of DSA-AI/ML Projects:<ul><li>DSA-AI/ML reference architectures.</li><li>Data visualization principles for DSA-AI/ML.</li><li>Federated Learning in large-scale DSA-AI/ML systems.</li></ul></li><li>Achievements, Challenges, Trends, and Future Research Directions on DSA-AI/ML Projects:<ul><li>Large multimodal model-based simulation game for DSA-AI/ML systems.</li><li>Value stream analysis and design applied to DSA-AI/ML systems.</li><li>Quality management 4.0 and AI for DSA-AI/ML systems.</li></ul></li></ul><p>Hence, this research-oriented co-edited book contributes to achieve the systematic development and implementation of Data Science, Analytics, and AI/ML systems.</p>

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Engineering and Management of Data Science, Analytics, and AI/ML Projects

  • 书籍

  • 发表日期：

    2026年

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摘要

This book presents a dual perspective on modern research and praxis on Data Science, Analytics, and AI/Machine Learning (DSA-AI/ML) system with small or big data. Consequently, potential readers—academics, researchers and practitioners interested in the systematic development and implementation of DSA-AI/ML systems—can be benefited with the high-quality conceptual and empirical research chapters focused on:

  • Foundations,  Development  Platforms, and Tools on Engineering and Management of DSA-AI/ML Projects:
    • DSA-AI/ML reference architectures.
    • Data visualization principles for DSA-AI/ML.
    • Federated Learning in large-scale DSA-AI/ML systems.
  • Achievements, Challenges, Trends, and Future Research Directions on DSA-AI/ML Projects:
    • Large multimodal model-based simulation game for DSA-AI/ML systems.
    • Value stream analysis and design applied to DSA-AI/ML systems.
    • Quality management 4.0 and AI for DSA-AI/ML systems.

Hence, this research-oriented co-edited book contributes to achieve the systematic development and implementation of Data Science, Analytics, and AI/ML systems.