Master of Science in
Data Science

About the programme

With an MSc in Data Science from the IT University of Copenhagen you will become a lead data scientist with advanced analytical and technical skills covering all aspects of handling, analysing, presenting, and operationalising data. You will build on your bachelor degree and further specialise the skills and knowledge that you acquired. You will gain a profound mathematical and algorithmic foundation for understanding emerging technologies, statistics, and computational challenges. You will gain insights on research problems, for instance in advanced natural language processing, deep learning, and network analysis. You will be equipped to discuss the ethical implications of such technologies and their impact on society. At the end of your MSc, you will be ready to apply the profound theoretical and applied knowledge to solve real world data science problems in the industry or academia.

The MSc in Data Science programme addresses the growing demand for data scientists across all industries. You will learn to derive insights from varied data across sectors and industries to harvest the knowledge needed to improve processes and create innovative solutions. You will learn how to apply your skills to solve societal and social problems.

The programme focuses on foundational aspects and applied technical skills within algorithms, machine learning, and advanced visualization. The programme emphasizes communication and ethical considerations as they play an important role in data handling and the emergent technology to be developed for the future societies.

As a graduate from this programme you will be in great demand across almost all industries and sectors. You will also be equipped to choose an academic career.

The programme is taught in English. 


Meet the Head of Programme

Hear Head of Programme, Barbara Plank, talk about MSc in Data Science and the competencies you acquire on this programme.

Who studies Data Science?

As a student in the Data Science programme, you should have a strong technical foundation from your bachelor’s degree (programming, data management, mathematics, machine learning). You should have a keen interest in applying your skills to derive insights from data and help solve problems of societal relevance and communicating solutions to stakeholders of diverse backgrounds.

Group work is essential in this programme, so you should be motivated to collaborate with and learn from fellow students.

Programme structure

The first three semesters of the programme are composed of mandatory courses and specialising elective modules and in the fourth semester you write a concluding master’s thesis.

Course of study for MSc in Data Science
1st  semester Algorithm Design
(7.5 ECTS)
Advanced Applied Statistics
(7.5 ECTS)
Data in the Wild: Wrangling and visualizing data
(7,5 ECTS)
Seminars in Data science
(7,5 ECTS)
2nd  semester Elective
(7.5 ECTS)
Advanced Machine Learning
(7,5 ECTS)
Data Science in Production
(7,5 ECTS)
Algorithmic Fairness, Accountability and Ethics
(7,5 ECTS)
3rd  semester Elective
(7,5 ECTS)
(7,5 ECTS)
(7,5 ECTS)
Research Project
(7,5 ECTS)

(15 ECTS)
4th  semester Master thesis
(30 ECTS)
Programming content
Mathematics content
Applications to real world problems
Social science content
Research and scientific focus

Mandatory courses:

Mathematical and algorithmic foundations

  • Algorithm Design
  • Advanced Applied Statistics & Multivariate Calculus
  • Advanced Machine Learning for Data Science

Exploration of heterogeneous data, advanced visualization, involvement of stakeholders in project-based courses

  • Data in the Wild: Wrangling and visualizing data
  • Data Science in Production 
  • Seminars in Data Science

Communication skills and ethical considerations 

  • Algorithmic Fairness, Accountability and Ethics
  • Research Project

Electives and Master's Thesis

The electives and the master’s thesis offer further opportunities for shaping your own profile. You can choose between a number of courses offered at the IT University at master level for electives, or even take electives at a different Danish or international university. The master’s thesis can be completed in groups or individually.




Teaching methods in the MSc in Data Science programme include lectures, project work, and assigned exercises. Group work is a big part of this programme, and you will be expected to apply what you learn in your group work.

The programme is taught in English and course material will be in English. Cases and examples from both Danish and international organisations will occur.


During your studies, you have the opportunity to take a semester abroad. Going abroad is a chance to further specialise your academic profile, experience a different study environment, and explore a new country.

  • Germany – TUM (Die Technische Universität München)
  • The Netherlands –  Maastricht University
  • Iceland – Reykjavik University
  • Czech Republic – Charles University

Career opportunities

With a MSc degree in Data Science you will be equipped to work in a wide range of sectors and industries where demand for Data Science graduates is high. You will also be eligible to pursue a PhD in areas such as Computer Science, Data Science, Network Science, Data Systems, Natural Language Processing.

Examples of job titles you could have include:

  • Lead Data Scientist
  • Data Architect
  • Data Engineer
  • Data Analyst
  • Data Science Consultant
  • Data Pipeline Architect
  • Business Intelligence Specialist

What can you do as a data scientist?

Data science in a consultancy

 What is a data scientist? Hear Mikkel Holm Sørensen, founder of the consultancy /KL. 7, explain how they work with data, and what data enables now and will do in the future.

How data can improve our health

What role does data play in the public sector? And what does data mean to public health in the future? Hear Head of the Health Data Agency (Sundhedsdatastyrelsen), Lisbeth Nielsen, explain what data is and how they use it to develop initiatives to improve public health.

What does a data scientist do at the Danish Mental Health Fund?

How can an NGO make use of data? And how does data improve their work? Hear what Maria Tersing Kristensen, fundraiser and data scientist at the Danish Mental Health Fund (Psykiatrifonden), uses data for.

Are you interested in studying at the IT University of Copenhagen, and do you have questions about programmes, student life or the like, please contact the Study and Career Guidance.