Data and Computationally Intensive Systems


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.


Increasingly large amounts of data are being collected that relate to societal and industrial processes. This data spans a variety of structures and includes tabular data and more complex, graph-structured data.

Successful value creation from such data involves data integration, preparation, and management, in addition to data analysis and machine learning  that supports data exploration and knowledge extraction. These are typically data and computationally intensive processes that call for advanced data processing, data analysis and machine learning.

Learning objectives


  • Knowledge about data preparation and processing techniques relevant for the project domain.

  • Knowledge about relevant data analysis and machine learning methods for solving data science problems involving data ranging from tabular data to¬† complex, graph-structured data.


  • Identify a concrete and relevant application domain for which one or more suitable data sources are available.

  • Develop a data science solution for an application domain.

  • Perform data preparation and apply data analysis and machine learning methods and analyze the results.

  • Document the developed solution and the results, including the knowledge gained about the domain.


  • Reason about relevant techniques and methodologies for integrating and processing available data.

  • Reason about relevant data analysis and machine learning methods.

  • Reflect on the applied methods and techniques as well as the results obtained.

Type of instruction

Project work



Name of examData and Computationally Intensive Systems
Type of exam
Oral exam based on a project
Assessment7-point grading scale
Type of gradingExternal examination
Criteria of assessmentThe criteria of assessment are stated in the Examination Policies and Procedures

Facts about the module

Danish titleData-og beregningsintensive systemer
Module codeDSNDVK101
Module typeProject
Duration1 semester
Language of instructionDanish and English
Empty-place SchemeYes
Location of the lectureCampus Aalborg
Responsible for the module


Education ownerMaster of Science (MSc) in Data Science and Machine Learning
Study BoardStudy Board of Computer Science
DepartmentDepartment of Computer Science
FacultyThe Technical Faculty of IT and Design