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 first two semester of the programme as well as other relevant analytical approaches – to a well defined business problem. Students are expected to consider perspectives on data driven business development, ethics & compliance as well as data engineering and model deployment.
Empirical semester project within business data science and ML deployment in collaboration with an external organisation (external partner collaboration is not required but highly recommended, and supported). The project departs from a real-life empirical problem and uses a suitable combination of methods and frameworks covered throughout the first two semesters to address it. If possible, the analysis is based on real data provided by the collaborating institution, possibly combined with other sources. Projects have to consider issues related to data engineering, deployment and other production-critical aspects.
After completion of the module, students are able to define an appropriate problem formulation within business 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 within previous modules and autonomously apply it to their specific problem.
The objective is that the student after the module possesses the necessary knowledge on:
The objective is that the student after the module possesses the necessary skills in:
The objective is that the student after the module possesses the necessary competences in:
For information see § 17.
|Name of exam
|Type of exam
Oral exam based on a projectGroup examination with max. 5 students.
|7-point grading scale
|Type of grading
|Criteria of assessment
|The criteria of assessment are stated in the Examination Policies and Procedures
|Language of instruction
|Location of the lecture
|Responsible for the module
|Study Board of Economics and Business Administration
|Aalborg University Business School
|Faculty of Social Sciences and Humanities