By overcoming all the conventional limitations associated with the synthesis of metalloid micro- and nanoparticles in aqueous media we present a new one-step approach to the synthesis of highly crystalline...
The article is devoted to the issues of managing education in end-to-end technologies, in particular big data analytics and artificial intelligence, in Russian universities. The article presents statistical data on the scale of the implementation of big data and artificial intelligence training programs in Russian universities. The authors note that to process a significant amount of information, algorithms for working with big data were used, such as Google Chrome extensions for extracting data from Instant data scraper and Table Capture web pages. Based on the results of the study, the key features of managing the development and implementation of training programs for big data and artificial intelligence in the top 15 universities of the country were identified and analyzed. It is noted that most of the programs have been developed “at the intersection” of academic disciplines and are aimed at training universal specialists, which dictates the integration of university faculties during their creation and close interaction with representatives of the professional community. Judgments are given that the most dense integration of universities and business is the automatic employment of students during the period of study. It is revealed that the management of the development of training programs for big data and artificial intelligence involves collaboration with EdTech platforms and the implementation of programs in a remote form that combines the advantages of a classical university program and the convenience of online learning, in particular, communicative comfort. The study showed that learning management also involves the development of “soft skills” among specialists in the field of data analytics and artificial intelligence.
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.
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