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Last update: RNDr. Jiří Mírovský, Ph.D. (09.11.2021)
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Last update: RNDr. Jiří Mírovský, Ph.D. (09.11.2021)
This course is a gentle, programming-free combination of lectures and practical demonstrations of real-life data workflows in various SSH research areas. It aims at motivating the SSH students to improve their digital literacy in more advanced data analytics courses. |
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Last update: RNDr. Jiří Mírovský, Ph.D. (09.11.2021)
To pass the course, students will be required to submit all of the six homework assignments. |
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Last update: doc. Mgr. Barbora Vidová Hladká, Ph.D. (05.01.2022)
Brett, M.R. Topic Modeling: A Basic Introduction. The Journal of Digital Humanities 2(1): 12-16. 2012. Foster, Ian, Ghani, Rayid, Jarmin, R.S., Kreuter, F. and Lane, J. (ed.). Big Data and Social Science: A Practical Guide to Methods and Tools (Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences). 2017. Piotrowski, Michael. Natural Language Processing for Historical Texts. Morgan & Claypool Publishers. 2012. |
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Last update: doc. Mgr. Barbora Vidová Hladká, Ph.D. (05.01.2022)
The course focuses on research-based learning about the data life cycle through existing data sets in several domains.
1) Digitizing data 2) Annotating data 3) Licensing data 4) Storing and searching data 5) Quantitative textual analysis in sociology 6) Using data in law 7) Using data in natural language processing 8) Visualizing data 9) Big data and digital libraries |
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Last update: RNDr. Jiří Mírovský, Ph.D. (09.11.2021)
This course does not require any prior data analysis or computer science experience. All you need to get started is basic computer literacy. |