This book explains data science in a unique way that allows the readers to not only learn data science theories easily, but also to practie (hand and machine computations) actual aplications of data science. The book is rich in diagrams and mind maps; avoids esoteric mathematical proofs and uses simple mathematical explanations; and includes calculations for small data and practical procedures for big data. The book is divided into 13 chapters covering data science models with rich contents, which include algorithms correlation analysis, cluster analysis, Bayesian classification, nearest neighbor method, decision trees, dimension reduction analysis, and regression models. The computational steps are presented using examples of small data, while the results are validated in R language. In addition, case data of big data is also available.