Building upon the knowledge introduced in The Data Science Framework, this book provides a comprehensive and detailed examination of each aspect of Data Analytics, both from a theoretical and practical standpoint. The book explains representative algorithms associated with different techniques, from their theoretical foundations to their implementation and use with software tools. Designed as a textbook for a Data Analytics Fundamentals course, it is divided into seven chapters to correspond with 16 weeks of lessons, including both theoretical and practical exercises. Each chapter is dedicated to a lesson, allowing readers to dive deep into each topic with detailed explanations and examples. Readers will learn the theoretical concepts and then immediately apply them to practical exercises to reinforce their knowledge. And in the lab sessions, readers will learn the ins and outs of the R environment and data science methodology to solve exercises with the R language. With detailed solutions provided for all examples and exercises, readers can use this book to study and master data analytics on their own. Whether you're a student, professional, or simply curious about data analytics, this book is a must-have for anyone looking to expand their knowledge in this exciting field.

This practical book shows the procedure to integrate, in a practical way, empirical propagation methods with geographical information systems (GIS) to obtain the radio coverage in open environments. It includes the theoretical explanation of empirical methods and GIS but as a basis to develop a real tool that combines both aspects to provide the user a suitable method for the wireless network planning in urban areas. The book introduces the empirical propagation methods and their application to wireless network planning. The motivation for combining them with the information obtained from geographical information systems is illustrated as well as their application to real situations. The most important empirical methods used to calculate the propagation in open environments are reviewed. Focus is given to the geometrical information needed to prove the necessity of obtaining some geographical information if these methods must be applied to realistic network planning. A review of the most important GIS is also described. The advantages and disadvantages of every system is analyzed from the point of view of its integration with an empirical propagation method. An application that combines a geographical information system with an empirical propagation method is fully described. The practical features of this integration are completely studied to allow an engineer to use and develop his own tool. Examples are given in each chapter to fully describe and illustrate the process.