This book is an introduction to concepts, techniques, and applications in data science. This book focuses on the analysis of data, covering concepts from statistics to machine learning, techniques for graph analysis and parallel programming, and applications such as recommender systems or sentiment analysis. All chapters introduce new concepts that are illustrated by practical cases using real data. Public databases such as Eurostat, different social networks, and MovieLens are used. Specific questions about the data are posed in each chapter. The solutions to these questions are implemented using Python programming language and presented in code boxes properly commented. This allows the reader to learn data science by solving problems which can generalize to other problems. This book is not intended to cover the whole set of data science methods neither to provide a complete collection of references. Currently, data science is an increasing and emerging field, so readers are encouraged to look for specific methods and references using keywords in the net.