About the course

The course aims to enable the student to critically process the collected data using graphic visualisation and various analytical methods, as well as communicate results from the collected data in an easily understandable way.

Course content

The course contains the following elements:

- organisation of data
- dimensionality reduction
- hidden patterns and clusters
- plotting techniques and mapping for visualisation of distributions, for relationships between variables, visualisation of categorical variables.
- data-based storytelling: influence, technique and ethics.

Syllabus and course literature

You can find a list of literature in the syllabus, along with other details about the course.

Entry requirements and selection

Entry requirements

Bachelor of Science in computer science or related subjects.

At least 15 credits in programming.

At least 7.5 credits in mathematics.

Knowledge equivalent to English 6 at Swedish upper secondary level.

Selection

University credits completed 100%

Course evaluation

The University provides students who are taking or have completed a course with the opportunity to share their experiences of and opinions about the course in the form of a course evaluation that is arranged by the University. The University compiles the course evaluations and notifies the results and any decisions regarding actions brought about by the course evaluations. The results shall be kept available for the students. (HF 1:14).

Contact

For more information about the education:

TSstudent@mau.se