Course: Data Science Seminar 2

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Course title Data Science Seminar 2
Course code KMA/DSS2
Organizational form of instruction Seminar
Level of course Bachelor
Year of study not specified
Semester Summer
Number of ECTS credits 2
Language of instruction Czech
Status of course Compulsory-optional
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Fürst Tomáš, RNDr. Ph.D.
  • Hron Karel, prof. RNDr. Ph.D.
  • Pavlačka Ondřej, RNDr. Ph.D.
Course content
The seminar will deal with current trends in bayesian inference, machine learning, applied mathematics, Data Science, etc. The aim of the seminar is to provide a platfomr for the communication among students, academic staff and professionals from outside Academia

Learning activities and teaching methods
Monologic Lecture(Interpretation, Training), Dialogic Lecture (Discussion, Dialog, Brainstorming)
Learning outcomes
To follow what is currently happening in the field of Data Science, if possible outside academia
Orientation in the world of Data Science
Prerequisites
Interest in the field of Data Science

Assessment methods and criteria
Student performance

Active participation at the seminar
Recommended literature


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester
Faculty: Faculty of Science Study plan (Version): Applied Mathematics - Specialization in Business Mathematics (2021) Category: Mathematics courses 3 Recommended year of study:3, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Applied Mathematics - Specialization in Data Science (2020) Category: Mathematics courses 3 Recommended year of study:3, Recommended semester: Summer
Faculty: Faculty of Science Study plan (Version): Applied Mathematics - Specialization in Industrial Mathematics (2020) Category: Mathematics courses 3 Recommended year of study:3, Recommended semester: Summer