Bi8700 Topics on data management, analysis and visualization

Faculty of Science
Spring 2020
Extent and Intensity
0/1/0. 2 credit(s). Type of Completion: z (credit).
Teacher(s)
RNDr. Martin Komenda, Ph.D. (lecturer)
Mgr. Matěj Karolyi (lecturer)
Mgr. Martin Víta (lecturer)
Guaranteed by
RNDr. Martin Komenda, Ph.D.
RECETOX - Faculty of Science
Contact Person: RNDr. Martin Komenda, Ph.D.
Supplier department: RECETOX - Faculty of Science
Prerequisites
General interest in a domain of data processing, analysis and visualisation.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 12 student(s).
Current registration and enrolment status: enrolled: 1/12, only registered: 0/12, only registered with preference (fields directly associated with the programme): 0/12
fields of study / plans the course is directly associated with
Course objectives
This course introduces selected topics from a domain of data processing, analysis and visualisation. 4 particular projects in a form of interactive workshops under the supervision of experts from practice will be organised. Each workshop will cover basics of the proven methodology and method for data mining. The active cooperation between students groups and mentors will be needed.
Learning outcomes
Student understands the need of systematic usage of data mining methodological background.
Student meets up-to-date trends in a domain of data processing, analysis and visualisation.
Student adopts new techniques during a solution of pilot research projects.
Syllabus
  • The topics for spring 2020 are the following:
  • Medical curriculum mapping
  • Open data: Data analysis and visualisation
  • Effective visualisation and data storytelling
  • Deep learning (2 blocks)
Teaching methods
Practical-oriented workshops blocks in a form of 3 hours long classes, which consist of interactive quizzes, simplified tasks, CRISP-DM application in practice, discussion in pairs).
Assessment methods
At least 80 % of attendance.
Language of instruction
Czech
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
The course is taught: in blocks.
The course is also listed under the following terms Spring 2019.
  • Enrolment Statistics (recent)
  • Permalink: https://is.muni.cz/course/sci/spring2020/Bi8700