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Artificial Intelligence

Master

How is Artificial Intelligence structured?

The master’s degree in Artificial Intelligence is studied over 2 years, and each academic year is divided into 2 semesters. You’ll have the chance to specialise through elective courses and projects, finishing with a master’s thesis. There’s also the option to undertake a company project during your studies.

The first year serves as your technical, analytical, and strategic foundation. You gain both a broad understanding and the first deeper skills that enable you to work with AI in a complex real-world context.

You begin by exploring how AI affects people, democracy, and society, while also learning to view technology through a business lens: What creates value, and how can potential be turned into practical solutions?

At the same time, you build strong data skills through work with data mining and Big Data, learning how to identify patterns, make informed decisions, and handle large datasets in practice.

Your technical level is raised step by step as you dive into advanced AI methods, cybersecurity, and programming disciplines, giving you the confidence to work with complex systems.

Throughout the year, you also learn how to lead technological initiatives and turn knowledge into action, and you gain your first experience with more independent study. Working with reinforcement learning gives you insight into how systems can be trained to learn through experimentation – and you have the opportunity to shape your academic profile through an elective that matches your interests.

1st semester

  • AI and Democracy (5 ECTS)
  • Business Understanding and Development (5  ECTS)
  • Datamining and Big Data (10 ECTS)
  • Advanced Topics in Artificial Intelligence Cybersecurity, and Programming Languages (10 ECTS)

2nd semester

  • Technology Management (10 ECTS)
  • Reinforcement Learning (10 ECTS)
  • Constituent elective (10 ECTS)

The second year is about deepening your knowledge and taking ownership of your academic development. You have the freedom to shape your path through elective courses that either broaden your perspective or give you more specialised expertise.

If you wish to explore a topic in even greater depth, you can combine electives with a specialisation project. This is where you truly begin to leave your own mark on your programme.

In the fourth semester, you complete the degree with your master’s thesis, where you bring together everything you have learned. Here, you demonstrate your ability to think critically, work independently, connect theory with practice, and produce knowledge that can be applied in real-world contexts.

3rd semester

  • Activities that broaden academic perspectives (10 ECTS)
  • Activities that broaden academic perspectives or Specialisation project (20 ECTS)

4th semester

  • Master’s thesis (30 ECTS)

Choices and options

Electives and project work are mainly placed in the 2nd year of the programme, giving you the opportunity to shape your academic direction. The 3rd semester has no compulsory courses and is, therefore, well suited for an exchange abroad or a company project.

The final semester is dedicated to the master’s thesis, which may, for example, be interdisciplinary or carried out in collaboration with a company.

  • If you are considering a exchange stay as part of your Master’s programme in Artificial Intelligence, the third semester is generally the most suitable time to go. In addition, during the fourth semester you have the option of completing your Master’s thesis partly or entirely abroad.

    An exchange stay offers valuable learning experiences. It can give you deep insight into other countries and cultures, and it can contribute to your personal development. It will be an experience you are likely to remember for the rest of your life if you choose to go.

    Our counsellors can help you find the destination that’s right for you.

  • You may choose a company project as a perspective‑broadening activity in the third semester of your Master’s programme.

    When you undertake a company project, you spend a semester either partly or entirely within a company or organisation, taking part in everyday work alongside the employed staff and completing the agreed tasks.

    The number of hours you spend at the workplace depends on how large a role the project plays in your study programme. In the Artificial Intelligence programme, a company project may carry 10, 15 or 30 ECTS credits.

A typical week

Below is an example of what a weekly timetable might look like for a student in the first semester of the MSc in Artificial Intelligence. Your workload and schedule may vary from week to week, and as a rule, teaching and learning activities can be timetabled on weekdays between 8:15 and 18:00.

Monday
Tuesday
Wednesday
Thursday
Friday
8-10
Advanced Topics in Artificial Intelligence, Cybersecurity, and Programming Tools
[group class]
10-12
Datamining and Big Data
[group class]
12-14
Business Understanding and Development
[common class]
12-14

Datamining and Big Data
[common class]
14-16
Advanced Topics in Artificial Intelligence, Cybersecurity, and Programming Tools
[common class]
16-18
AI and Democracy
[group class]

Academic culture in Denmark

Danish academic culture is characterised by active participation in class, group work and critical thinking. Rather than simply accumulating and reproducing knowledge, you will be expected to analyse, question and discuss the course topics.

The relationship between lecturers and students is often rather informal; students and lecturers may find themselves joking together and engaging in vigorous debates during classes and lectures.

Studerende på Syddansk Universitet