SUMMARY
The article describes the relevance and feasibility of implementation Data Science courses for leading economics majors: 051 Economics, 075 Marketing, 073 Management. Application of computer technology, mathematical methods and models, statistical analysis in the study process for economics students became routine long time ago, then why is Data Science linked mostly only to the faculties of information technologies? The specificity of economic professions requires the acquisition of skills in the work with large data sets, qualitative evaluation of statistics, predicting a large number of economic phenomena, so the economist of the future should be not only a specialist in the main subject area, but also a specialist in Big Data and Data Mining. The study outlines the underlying background for essential changes. The article analyzes relevant educational and professional programs, blocks of disciplines, providing qualitative assimilation of new information by students and acquisition of those abilities and skills that are needed by the modern specialist in the field of economy and will form student as a serious competitor in the labor market. It has been conducted the analysis of modern international commercial on-line courses, specifying the topics and aspects necessary for the future economics graduates. The logical scheme of Data Science specialties introduction which follows the relevant cycle of the existing disciplines of general and professional training is proposed. Mastering the knowledge of qualitative data analysis and tools for optimal work with them should be one of the main tasks of the methodological system of education and research at the faculties of economics. Modern educational technologies and scientific facilities of universities should help to expand the understanding and perception of the economist, marketologist, and manager profession, because the digital advertising, SMM, social networks, online applications, project management, State in a Smartphone, and other rapid transformations encourage to train not classic specialists, but universals who will be able to adapt quickly to the needs of the future.