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Lecturer(s)
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Tomovski Zhivorad, prof. Ph.D.
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Vodák Rostislav, RNDr. Ph.D.
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Burkotová Jana, Mgr. Ph.D.
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Dhara Raj Narayan, Ph.D.
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Vencálek Ondřej, doc. Mgr. Ph.D.
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Pavlačka Ondřej, RNDr. Ph.D.
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Fačevicová Kamila, Mgr. Ph.D.
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Hron Karel, prof. RNDr. Ph.D.
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Fürst Tomáš, RNDr. Ph.D.
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Course content
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The seminar leads students to read professional texts. The seminars may include prestigious scientific periodicals that are not narrowly defined in the field (Nature, Science, ...). Each week we choose one article, we all read it and one of the students presents it at the next seminar. A discussion will follow. The seminar will spread scientific horizons, but has the ability to communicate on topics that are outside the field of specialization. To be experts in Data Science, this is a key competence, because all the data the graduates will have the opportunity to meet, will occur naturally from scientific fields, where the graduates will not be experts.
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Learning activities and teaching methods
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Dialogic Lecture (Discussion, Dialog, Brainstorming)
- Homework for Teaching
- 20 hours per semester
- Attendace
- 26 hours per semester
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Learning outcomes
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Discussion of selected publication outputs in Data Science.
Synthesis Orientation in hot Data Science topics.
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Prerequisites
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Interest in Data Science.
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Assessment methods and criteria
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Seminar Work
Active participation in the seminar - presentation of a scientific article.
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Recommended literature
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Aktuální časopisecká literatura..
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