Basic concepts of data science. Preparation and analysis of data. Modeling based on data. Analysis of results. Visualization of data. Predictions and evaluations. Classification. Big data analysis. Statistical deriving conclusion. Statistical tests. Sampling correlation and regression. Modeling based on computer intelligence (artificial neural networks, decision trees, associative rules, fuzzy logic, support vector machine, genetic algorithm, etc.). Expert systems. Application of data science in different fields. Ethical aspects of data science. Part of the teaching on the subject is done through independent research and study work in the field of data science. Research and study work includes active monitoring of primary scientific sources, possibly writing a paper on data science.