About the course

The purpose of the course is to provide the student with an understanding of how digital methods support business development and social innovation in finding patterns and insights from a large amount of data. Based on concrete cases, the student will learn basic concepts of how to select and apply adequate digital methods for the data mining, pre-processing, classification, segmentation, grouping, modelling, visualization, evaluation and analyzation of digital data. The student will work with cases that focus on Social Innovation in order to find solutions and improvements to social problems and needs in society.

Course content

Entry requirements and selection

Entry requirements

30 credits Informatics of which at least 7.5 credits in programming, or 30 credits Computer and Information Science of which at least 7.5 credits in programming, and English 6.


University credits completed 100%

Course literature

Course evaluation

At the end of the course, all students will be offered the opportunity to submit written comments on the course. A compilation of these comments and any remarks from the course coordinator will be discussed with students/course representatives at a course evaluation/programme committee meeting. The compilation will be made available on the department network. (HF 1:14)