Studerende på ITU

Data Science

The programme

With a BSc in Data Science, you will become the next generation analyst — a data scientist with comprehensive analytical and technical skills covering all aspects of handling and analysing data. By deriving key insights from data, you will be driving and informing decision-making of the future. You will learn to work in interdisciplinary teams and not only make sense of vast amounts of data, but also use your organisational knowledge and market understanding to make a difference.

Businesses and other organisations worldwide are accumulating enormous quantities of data for software or market research, disaster prediction, investment analysis, policy development, artificial intelligence, preventive initiatives in health and much more. However, there is a widespread lack of professionals with the know-how to harvest intelligence from this data.

During the three-year programme, you will get extensive teaching in the technical subjects mathematics and statistics for data sciences, programming, machine learning, algorithms development, and data management, as well as in social science applications, research methods, data visualisation, communication, and critical reflection.


This will ensure the comprehensive interdisciplinary knowledge you will need as a data scientist. Here are some examples of potential student projects:

  • Network analysis: election prediction via social media topic modelling
  • Facebook analysis: detecting friends and enemies in social networks over millions of users
  • Language analysis: detecting contradictions in live debates
  • Recommendation systems: personalised automated product recommendation systems for e-commerce
  • Marketing design: automated accurate target group analysis for marketing campaigns over millions of users

The Data Science programme is taught in English. Courses rely on cases and examples from both Danish and international organisations. 

Noncurricular events at the university may be held in Danish.

With a bachelor degree in Data Science you have direct access to the MSc in Data Science.



 

Meet students from Data Science

Meet Data Science student Anders who talks about how theory and practice go hand in hand in the programme.

Meet Marie-Louise who studies Data Science and plays golf at an elite level. Learn more about the programme and what her studies and her elite sport have in common.

Yasmin dreams about using her degree in Data Science to work in healthcare. At the age of 11, Yasmin was diagnosed with a chronic disease but that has not kept her from following her dreams.

Is this programme for you?

Studying Data Science requires strong math skills, as well as an interest in analysing real-world problems in business-life, science, and society. You will be able to apply your curiosity and interest in making new discoveries when you work on the various cases. 

The IT University is continuously in dialogue and collaboration with relevant industries, ensuring that you acquire skills in demand by the business world. During your studies you will develop new technical skills within statistics and computer science. There is a great deal of group work in this programme, so you should be motivated to collaborate with other students.


  

Virtual Open House 2025

Watch the virtual Open House for our BSc Data Science programme. Head of Programme Therese Graversen introduces the program, followed by a Q&A with the interim Head of Programme Michele Coscia and Tetiana, a Data Science student, covering programme details, student life, and studying in Denmark.

Programme structure

The bachelor programme in Data Science is a three-year full-time study with a focus on mathematics and statistics, computer science, and applied social science. Through extensive project work, students are trained in applying these skills in realistic settings, including interacting with domain experts and decision makers in the industry to formulate relevant goals and to support data-driven decision-making processes.

See curriculum for BSc in Data Science.

Shared Curriculum: Rules and Regulations

Study structure

1. semester

Introduction to Data Science and Programming
(15 ECTS)
Linear Algebra and Optimisation
(7.5 ECTS)
Foundations of Probability
(7.5 ECTS)

2. semester

Applied Statistics
(15 ECTS)
Algorithms and Data Structures
(7.5 ECTS)
Projects in Data Science
(7.5 ECTS)

3. semester

Machine Learning
(15 ECTS)
Introduction to Database Systems
(7.5 ECTS)
Network Analysis
(7.5 ECTS)

4. semester

Natural Language Processing and Deep Learning
(15 ECTS)
Data Visualisation and Data-Driven Decision-making
(7.5 ECTS)
Large-Scale Data Analysis
(7.5 ECTS)

5. semester

Technical Communication
(7.5 ECTS)
Security and Privacy
(7.5 ECTS)
Data Science in Production: MLOps and Software Engineering
(7.5 ECTS)
Elective
(7.5 ECTS)

6. semester

Bachelorprojekt
(15 ECTS)
Reflections on Data Science
(7.5 ECTS)
Elective
(7.5 ECTS)
Applikationer til problemer i den virkelige verden
Matematisk indhold
Programmeringsindhold
Samfundsvidenskabeligt indhold

Electives and bachelor project

The electives and the bachelor project provide you with an opportunity to shape your own profile. As electives you may choose between a number of courses offered at the IT University at bachelor’s level or even complete coursework at a different Danish or international university. The bachelor project may be conducted in groups or individually.

See a description of all courses offered at the IT University.

ECTS and workload

One ECTS corresponds to approximately 27.5 hours of work for the students, in line with the official European Credit Transfer System.

A 7.5 ECTS course therefore represents around 206 hours of activity in total. These hours include contact hours (teaching and supervision), individual study time, group work and exam activities, corresponding to an average of approximately 10 hours per week from the first day of teaching to the last day of the exam period. In practice there will be fluctuations, as there often is more work required during teaching weeks and when working on projects.

More

Hide

Teaching

The programme has a considerable element of "hands-on" project work allowing you to develop your skills in realistic and complex settings. The teaching will alternate between this kind of project work, lectures, and exercises.

The Data Science programme is taught in English. Case studies will include both Danish and international examples.

Studerende på DS

Learn more about Data Science

Project example

Lisa and her group use math and programming in practice to analyse data from companies.

IT can change the world

Margrethe follows her heart. She wants to use her degree in Data Science to make a difference in the world. Hear her explain how.


A talk with chairperson for Council of Ethics

ITU student Nadia meets Anne-Marie Gerdes, chairperson of the Danish Council of Ethics, for a talk about artificial intelligence and how to use data in a responsible manner.

Further education

With a bachelor's degree in Data Science you will hold the academic title of BSc (Bachelor of Science).

This qualifies you to continue your studies in a master’s programme at the IT University or a different Danish or foreign university in the areas of science, social science, and technology.

You will have direct access to the MSc programme in Data Science at the IT University. You have direct access for three years after graduation (legal right to admission).

Additionally, the bachelor degree in Data Science qualifies you for entry in the following MSc programmes at the IT University: Computer Science (provided specific CS electives), Digital Innovation & Management (provided Danish A), and Games

Career options

After you have finished your bachelor's degree in Data Science, you may choose to go straight out onto the job market. The programme provides you with skills and knowledge that are in high demand across a wide variety of industries and in both private and public sectors.

The BSc programme in its entirety qualifies you to work as a data scientist within a wide array of fields, from investigative journalism where you analyse data to find stories, to financial modelling, financial fraud prediction, urban planning, forensics, agriculture, social media analysis, remote sensing, international development, and much more.

Examples of job titles:

  • Data scientist
  • Machine learning engineer
  • Business intelligence analyst
  • Data analyst
  • Digital analyst

Career portrait

Meet Jean-Marie, who studied Data Science at ITU and now is working at PwC. Hear him explain why he chose to study Data Science and how he uses the degree in his job.

Therese has completed a bachelor's degree in Data Science and currently works as a journalist at Ingeniøren's IT media Version2. Already as a student, Therese started working with journalism and data in the media world, and she was involved in uncovering the teledata case in 2019.


Activities for students on BSc in Data Science

Study Lab

Study Lab is open three times a week throughout the first semester. Study Lab is a place where you can get help with topics covered in your courses, e.g. by discussing academic themes that you are curious about or getting help with difficult material.

Study Lab additionally hosts interesting activities such as review sessions, minor courses on relevant but noncurricular topics, as well as professional lectures with external speakers. Study Lab is run by experienced ITU students.

Live Coding

Live Coding is a forum for first semester students in Data Science. Here you receive hands-on experience with programming through sessions where a teaching assistant will show you how coding can be done by actually writing the code with you and the other students.

Live Coding takes place once a week from the beginning of every semester.

 

 


Student exchange

You have the opportunity to complete part of your programme at a university abroad. Especially the fifth semester is well suited for an exchange. This is a chance for you to further specialise your education and gain experience working in a different culture.

The IT University has exchange agreements around the world. Students enrolled in BSc Data Science, may among other places study a semester at one of the following universities:


  • Australia – University of Technology Sydney
  • China – City University of Hong Kong
  • Germany – Technical University of Munich
  • NED – Maastricht University
  • Netherlands – Maastricht University
  • New Zealand – Auckland University of Technology
  • South Korea – Dankook University
  • Spain – Polytechnic University of Catalonia – Barcelona School of Informatics 
  • Switzerland – Universitá della Svizzera italiana

Admission figures

 

2025

  • Admission GPA, quota 1: 3.0
  • Number of applicants (of which in quota 2): 648 (463)
  • Number of admitted students: 104
  • Distribution of admitted students, quota 1/quota 2, %: 80/20
  • Distribution of admitted students by nationality (Denmark/international), %: 27.8/72.2
  • Average age of admitted students: 21.8
  • Gender distribution, female/male (based on CPR), %: 34.6/65.4
  • Available spots: No

2026

  • Distribution of admitted students, quota 1/quota 2, %: 80/20

Note: ITU only has summer admission and does not offer standby-by list in connection with the admission process.

Kontakt studievejledningen på ITU

Study and career guidance

It’s completely normal to have questions when choosing a degree. Our student advisors are ready to guide you—whether it’s about student life, admissions, or study plans. We can, for example, advise you on:

  • Student life at ITU – what is everyday life like as a student?
  • The admissions process – how do you apply?
  • Career paths – what different opportunities might be available after your studies?
Contact a study advisor

Follow @itustudent on Instagram and meet more ITU students

Alberte
Anton
Ayush
Josefine
Ezeguiel
ITU takeover med to studerende
Malgosia
Malthe
Nicholas
Renia
Rikke
Jasmin