EduSinglePage
Course offered as a part of a programme
Course, master’s level
7.5 credits
Malmö | daytime | 50%
11 November 2024 - 19 January 2025
Course code: DA630E
About the course
The purpose of the course is for the student to develop an understanding of the societal consequences (risks and favourable opportunities) of today's increasing digitalisation, and to be able to convey knowledge about methods and tools in the field of data science, with significance for decision making and societal development.
This course is offered as part of programme:
Course content
The course contains the following elements:
The course focuses on how modern information technology and data processing gives rise to new kinds of ethical dilemmas. The course uses case studies to convey principles and guidelines for managing:
- Data quality
- Data integrity and responsible management of sensitive data (e.g. GDPR, consent)
- Data security (including data ownership, block chain techniques, threats and risk analysis)
- Data-driven and evidence-based decision making
- Neutrality, transparency, reliability, accountability and personal self-determination in a data-driven society.
- Interpretability in machine learning models
- Susceptibility to bias and discrimination as a potential effect of information systems replacing manual processing
- Ethical perspective on data science
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
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).
