From Data to Science
2025/2026
Content, progress and pedagogy of the module
Disclaimer.
This is an English translation of the module. In case of
discrepancy between the translation and the Danish version, the
Danish version of the module is valid.
PURPOSE
he student will learn how to use data analysis and related modeling
as an essential part of problem-solving and gain further experience
in problem-oriented project work in a group.
JUSTIFICATION
In the project, data must be collected, for example, using
questionnaires or generated data, for example, through simulation.
The data must then be analyzed. The project can either focus on
algorithmic methods for simulation and data generation or focus on
statistical analysis of collected data.
Learning objectives
Knowledge
- Explain algorithmic methods for simulation and data generation and/or statistical analysis of collected data.
- Understand and explain the conducted data analysis.
Skills
- conduct a major data collection, e.g., using questionnaires, or generate data, e.g., through simulation
- conduct a major data analysis and reasonably ensure that it corresponds to the problem statement
- be able to use relevant project management tools, e.g., for version control
Competences
- define a problem and within this problem formulate and defend an issue that can be solved using data collection and data analysis as a significant part of the solution method
- develop a model that can be used in connection with solving the chosen problem
- describe how the data analysis solves a formulated problem within the context of the problem
- include relevant practical and social aspects of solutions within data science
- describe, reflect on, and analyze the experiences gained with problem-oriented project work in a group
Type of instruction
Project work
Extent and expected workload
The student is expected to spend 30 hours per ECTS, which for this activity means 300 hours.
Exam
Exams
| Name of exam | From Data to Science |
| Type of exam | Oral exam based on a project
As part of the project’s problem-solving, the group must
collaboratively develop a high-quality data analysis. The overall
design of the solution, possibly with an emphasis on techniques and
algorithms used, must be specifically explained.
As documentation for the project work, the project group must: - prepare a report - prepare a process analysis Midway through the project period, a status seminar will be held where the project group presents its problem statement, work results, and experiences with the project work process. At this seminar, at least one other project group and their respective supervisors will participate. |
| ECTS | 10 |
| Permitted aids | Aids (if any) will be posted on the course page in MOODLE |
| Assessment | 7-point grading scale |
| Type of grading | External examination |
| Criteria of assessment | The criteria of assessment are stated in the Examination Policies and Procedures |
Additional information
Contact: Study Board for Computer Science via cs-sn@cs.aau.dk or 9940 8854
Facts about the module
| Danish title | Fra data til videnskab |
| Module code | DSNDVMLB231 |
| Module type | Project |
| Duration | 1 semester |
| Semester | Spring
|
| ECTS | 10 |
| Language of instruction | Danish and English |
| Location of the lecture | Campus Aalborg |
| Responsible for the module |
Organisation
| Education owner | Bachelor of Science (BSc) in Data Science and Machine Learning |
| Study Board | Study Board of Computer Science |
| Department | Department of Computer Science |
| Faculty | The Technical Faculty of IT and Design |
