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| dc.contributor.author | Volkova, Nataliia P. | |
| dc.contributor.author | Rizun, Nina O. | |
| dc.contributor.author | Nehrey, Maryna V. | |
| dc.date.accessioned | 2019-09-14T17:29:35Z | |
| dc.date.available | 2019-09-14T17:29:35Z | |
| dc.date.issued | 2019-09-09 | |
| dc.identifier.citation | Volkova N. P. Data science: opportunities to transform education [Electronic resource] / Nataliia P. Volkova, Nina O. Rizun, Maryna V. Nehrey // Cloud Technologies in Education : Proceedings of the 6th Workshop on Cloud Technologies in Education (CTE 2018), Kryvyi Rih, Ukraine, December 21, 2018 / Edited by : Arnold E. Kiv, Vladimir N. Soloviev. – P. 48-73. – (CEUR Workshop Proceedings (CEUR-WS.org), Vol. 2433). – Access mode : http://ceur-ws.org/Vol-2433/paper03.pdf | uk |
| dc.identifier.issn | 1613-0073 | |
| dc.identifier.uri | http://elibrary.kdpu.edu.ua/xmlui/handle/123456789/3241 | |
| dc.identifier.uri | https://doi.org/10.31812/123456789/3241 | |
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| dc.description.abstract | The article concerns the issue of data science tools implementation, including the text mining and natural language processing algorithms for increasing the value of high education for development modern and technologically flexible society. Data science is the field of study that involves tools, algorithms, and knowledge of math and statistics to discover knowledge from the raw data. Data science is developing fast and penetrating all spheres of life. More people understand the importance of the science of data and the need for implementation in everyday life. Data science is used in business for business analytics and production, in sales for offerings and, for sales forecasting, in marketing for customizing customers, and recommendations on purchasing, digital marketing, in banking and insurance for risk assessment, fraud detection, scoring, and in medicine for disease forecasting, process automation and patient health monitoring, in tourism in the field of price analysis, flight safety, opinion mining etc. However, data science applications in education have been relatively limited, and many opportunities for advancing the fields still unexplored. | uk |
| dc.language.iso | en | uk |
| dc.publisher | Arnold E. Kiv, Vladimir N. Soloviev | uk |
| dc.subject | data science | uk |
| dc.subject | high education | uk |
| dc.subject | clustering | uk |
| dc.subject | natural language processing | uk |
| dc.subject | text mining | uk |
| dc.title | Data science: opportunities to transform education | uk |
| dc.type | Article | uk |
