Springer Data Analytics: A Theoretical and Practical View

Expand your understanding of data science with this comprehensive guide from Springer. Building upon the foundation laid in The Data Science Framework, this book offers a deep look into the many aspects of Data Analytics from both theoretical and practical perspectives. It is an essential resource for anyone looking to master representative algorithms and understand their implementation through various software tools. This text is specifically structured for educational settings, serving as an ideal textbook for a Data Analytics Fundamentals course. The content is organized into seven chapters designed to cover a 16-week lesson plan. By combining theoretical foundations with practical exercises, this book helps learners bridge the gap between abstract concepts and real-world application. Whether you are studying the mathematical basis of an algorithm or learning how to use it in a software environment, this book provides the detailed examination needed for academic and professional success in the field of computer science.