Overview of data science key concepts and the use of tools for data retrieval, analysis, visualization, and reproducible research. Topics include an introduction to inference and prediction, principles of measurement, missing data, and notions of causality, statistical traps, and concepts in data ethics and privacy. Case studies illustrate the importance of domain knowledge.