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Dátová veda a jej aplikácie
Data sheet
| Contributions: | Ľubomír Antoni, Ján Paralič, Peter Butka, František Babič, Martin Sarnovský, Peter Bednár, Peter Gurský, František Galčík, Miroslav Opiela, Ondrej Krídlo, Miron Kuzma, Erik Bruoth, Juraj Šebej, Tomáš Kekeňák, Gabriela Andrejková, |
| Spoluautori | Dušan Šveda, Jozef Kapusta, Martin Drlík, Michal Munk, Ľubomír Benko, Martin Vozár, Vladimír Siládi, Michal Vagač, Peter Jankovič, Miroslav Kvaššay, Michal Kvet, Michal Varga |
| Year of publication: | 2020 |
| Available from: | 20.10.2020 |
| Edition: | 1st edition |
| Document type: | Academic textbook - scripts |
| Publication language: | Slovak |
| Number of pages: | 188 |
| Faculty: | Faculty of Science |
| Note: | Tento projekt sa realizuje vďaka podpore z Európskeho sociálneho fondu v rámci Operačného programu Ľudské zdroje. Spracované s finančnou podporou národného projektu IT Akadémia – vzdelávanie pre 21. storočie |
| Licencia: | Creative Commons BY (Uveďte autora) |
More info
In university textbooks, we present the history of data science, basic concepts in artificial intelligence, machine learning, or deep learning. We describe the relationships between data science and other disciplines and summarize the tasks of the data scientist. We present an overview of university subjects in the field of data science, which were created and innovated at Slovak universities within the national project IT Academy - Education for the 21st Century. We present extended subject annotations, application examples and case studies using various methods in the field of data science. University textbooks are intended for students of bachelor's, master's, engineering and doctoral study programs in computer science, but also in non-informatics fields.
