The Modern World Landscape of Data Science Online Education - V. S. Nikolskiy; M. A. Lukashenko; E. A. Sharova (Высшее образование в России)
Data science as an emerging branch of applied knowledge and a new field of study is showing a strong momentum. Besides, the corresponding sphere of educational research is actively developing. At the same time, most of the scientific publications are aimed at studying specific issues related to the content of the programs and their methodological support. The wider context and especially the international perspective are lacking for the necessary attention of researchers.In this regard, the purpose of our study was to summarize and systematize information about training programs in the field of data science presented on online platforms of the main macro-regions – America, Europe and Asia. For this purpose, we found out what elements the corpus of data science training programs consists of, as well as how courses are distributed on educational platforms by countries, organizational providers, level of education and duration of study. Based on the data obtained, we conducted a comparative interregional study of educational programs presented on online platforms.The findings made it possible to draw conclusions about the specifics of the global landscape of data science online education, as well as to determine the specifics of the Russian segment and to formulate recommendations for solving significant problems of the domestic economy using data science online education.