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MSc · 120 ECTS · English · IT University of Copenhagen

MSc in Data Science

Every course on the ITU curriculum for this programme, by semester, the way the university publishes it. Student jobs matched to these courses appear here as they are indexed.

8 courses indexed1 curriculum versionTaught in English
Programme structure on itustudent ↗Official programme page ↗Curriculum (PDF) ↗

Curriculum

120 ECTS across 4 semesters
Curriculum version · pick your enrolment year

1st semester · Autumn

30 ECTS

2nd semester · Spring

30 ECTS

3rd semester · Autumn

30 ECTS
  • ElectiveChosen from the programme's pool · options on itustudent
    7,5 ECTS
  • ElectiveChosen from the programme's pool · options on itustudent
    7,5 ECTS
  • Research projectPrerequisite: Data in the Wild Wrangling and Visualizing Data · Seminars in Data Science
    7,5 ECTS
  • ElectiveChosen from the programme's pool · options on itustudent
    7,5 ECTS

4th semester · Spring

30 ECTS
  • ThesisPrerequisite: Research project
    30 ECTS
Notes from the curriculum
  • Choose a 7,5 ECTS course among the courses offered for the MSc in Data science. The module can also be used for writing a project under supervision.

What a graduate can do

The programme's own objectives, as written in the ITU curriculum in force from admission 2025. This is the language employers will read your coursework in.

Knowledge and understanding
  • Theory and practice within data-science specific areas of mathematics (principles of advanced statistical analysis, inference and calculus).
  • Theory and practice within data-science specific areas of scalable computing and data analytics (e.g., algorithm design, advanced visualization, data acquisition, learning from heterogeneous including unstructured data sources) and its applications to real-world scenarios.
  • Principles of ethics and fairness within Data Science.
  • Theory, scientific methodology and scientific issues within data science in the above areas at the highest international research level.
Skills
  • The graduate can master a state-of-the-art modern programming language and tools/frameworks to implement and develop software for data analysis.
  • The graduate can apply, assess and develop fundamental processes and practices to solve problems in data science. This includes the evaluation of theoretical issues of problems in data science to select, apply, implement and design scalable algorithms for 2 fundamental data analysis (e.g., in machine learning and statistical inference) and their adequate empirical validation.
  • The graduate is able to communicate, visualise and discuss the acquired data-driven knowledge with both academic peers and non-specialists.
Competences
  • The graduate can design and develop new solutions to enhance existing complex data systems, and combine and select different analysis methods in complex and unpredictable settings.
  • The graduate can independently initiate collaboration and work professionally with both data science peers and others in complex and inter-disciplinary contexts.
  • The graduate can independently take responsibility for own professional development based on theoretical knowledge and practical experience to advance and adapt own competencies to future needs.

Source: KDS-Curriculum-2025-in-force-from-admission-2025-pdf.pdf

studyjob.ai is not affiliated with the IT University of Copenhagen. The official programme structure and curriculum on itustudent.itu.dk govern; this page reproduces course facts (titles, codes, ECTS, semesters, prerequisites) as collected on 10 September 2026 and links to the university's own course descriptions. Spotted an error? ops@studyjob.ai