Social Data Science Semester Project


Content, progress and pedagogy of the module

This module aims at providing the student with an opportunity to apply a set of data science methods – a combination of techniques covered in the previous modules as well as other relevant analytical approaches – to a well defined problem.

The project departs from a real-life empirical problem and uses a suitable combination of methods and frameworks covered throughout the semester. If possible, the analysis is based on real data provided by a collaborating institution, possibly combined with other sources.

After completion of the module, students are able to define an appropriate problem formulation within social data science, identify a sophisticated data collection and analysis strategy, carry out the analysis and present their results using state-of-the-art data science approaches, as well as critically self-evaluate their findings. They can select the most suitable among the wide range of methods presented in previous modules autonomously apply it to their specific problem.

Learning objectives


The objective is that the student after the module possesses the necessary knowledge on:

  • theoretical and practical opportunities and challenges of applying different perspectives, methods and approaches to a central problem within social data science.
  • how to define relevant real-world empirical problems within data driven development.
  • showing insights in potential limitations of the undertaken analysis.


The objective is that the student after the module possesses the necessary skills in:

  • dentifying and delineating a problem that can be analysed using data science approaches.
  • Developing and carrying out a social data science project including data collection, preprocessing, modeling, and performance assessment.
  • Visualising, presenting and discussing results written and orally at an appropriate academic level.


The objective is that the student after the module possesses the necessary competences in:

  • independently initialising, controlling and completing problem-oriented social data science project work.
  • coordinating own resources for the solution of domain-specific related problems.
  • taking responsibility for own professional learning and development.

Type of instruction

For information see § 17.



Name of examSocial Data Science Semester Project
Type of exam
Oral exam based on a project
Group examination with max. 4 students. The student may also choose to write the project alone.
Assessment7-point grading scale
Type of gradingExternal examination
Criteria of assessmentThe criteria of assessment are stated in the Examination Policies and Procedures

Facts about the module

Danish titleSocial Data Science semesterprojekt
Module codeKADAT202212
Module typeProject
Duration1 semester
Language of instructionEnglish
Location of the lectureCampus Aalborg
Responsible for the module


Education ownerMaster of Science (MSc) in Economics and Business Administration
Study BoardStudy Board of Economics and Business Administration
DepartmentAalborg University Business School
FacultyFaculty of Social Sciences and Humanities