Data Science in Research, Business and Society
This course will provide students with a substantive discussion of applications and opportunities for data science in addressing real world problems coupled with an overview of field-specific research approaches for addressing these problems.
There are two sides to data. On the one hand, researchers and analysts can look to data as a source of insight and an object that can be manipulated to produce outcomes that can then be interpreted or acted upon. On the other hand, people produce data in the course of living without much ability to control what effect the traces we produce might have on our lives and futures.
The goal of this course is to relate the technical content of other courses to critical concerns about data and data science approaches. Students will learn different ways people might think about data in business, research and society at large.
The topics and approaches covered in this course include but are not limited to:
- Domain-specific approaches to asking questions along with the reasons for why questions might need to be asked differently
- Translating technical concepts to real-world concerns through research-based language
- Knowledge claims in different research traditions
- Empirical methodologies in different research traditions
- Ethical implications of data-driven practices
Formal prerequisitesThe course is mandatory for first semester BSc in Data Science students. Please note that this course is only available for students enrolled in the BSc in Data Science.
Intended learning outcomes
After the course, the student should be able to:
Ordinary examExam type:
C: Written report, internal (7-trinsskala)
Students will produce an individual report on a specific real world application of data science approaches, chosen from a pre-given list of domains and supplementary literature.