Official course description, subject to change:

Preliminary info last published 15/11-23
Course info
Language:
English
ECTS points:
7.5
Course code:
BSPRDAS1KU
Participants max:
91
Offered to guest students:
no
Offered to exchange students:
no
Offered as a single subject:
no
Programme
Level:
Bachelor
Programme:
BSc in Data Science
Staff
Course semester
Semester
Forår 2025
Start
27 January 2025
End
30 May 2025
Exam
Exam type
ordinær
Internal/External
intern censur
Grade Scale
7-trinsskala
Exam Language
GB
Abstract

This course aims to familiarize students with the pipeline for a Data Science project: from a domain-specific context and associated data we need to identify and formulate a domain-specific research question and translate it into a technical problem, which can then be addressed with techniques within Data Science. After performing the relevant data analysis, the results should be communicated in the context of the domain.

Description

The course consists of a Data Science project from start to finish, including the initial problem presentation, technical translation of the problem, some methodology decisions, implementation, evaluation, and translation of the results back into non-technical language. Through this course students will gain experience with online collaboration using platforms such as GitHub and Overleaf.

Formal prerequisites

This course combines knowledge from the first-semester courses Introduction to Data Science and Programming, Linear Algebra and Optimisation, and Foundations of Probability with knowledge that will be acquired during the second semester from the two concurrent courses.

The course is only open for students enrolled in BSc in Data Science.


Intended learning outcomes

After the course, the student should be able to:

  • Identify and delimit a problem in Data Science within a given domain-specific context
  • Discuss the relevant options for an appropriate scientific methodology to address the problem; this covers considerations on the data-analytical approach and on the implementational approach
  • Carry out the full analysis according to the selected methodology
  • Communicate their work to both experts and non-experts; this should cover the entire pipeline from problem formulation to analysis methods and their results
Ordinary exam
Exam type:
D: Submission of written work with following oral, Internal (7-point scale)
Exam variation:
D2G: Submission for groups with following oral exam supplemented by the submission. Shared responsibility for the report.