Master's Programme in Artificial Intelligence

While studying

The Master’s programme in Artificial Intelligence equips you with the essential knowledge and practical skills to navigate this transformative information technology field:

1. Foundational Understanding: Delve into the core principles of AI, exploring its capabilities, limitations, and societal impact.

2. Design and Build: Learn how to create robust AI systems that adhere to an ethical context. You’ll be equipped to develop solutions that empower users while minimizing unintended consequences.

3. Responsible Application: Gain insights into the responsible deployment of AI. Understand the importance of transparency, fairness, and privacy in AI systems.

Join us on this exciting journey toward shaping a future where AI serves humanity ethically and responsibly!

Programme focusing on Trustworthy AI

This is the first Master’s programme in Artificial Intelligence (AI) in Sweden with a focus on Trustworthy AI. Trustworthy AI is the kind of AI that aims to be Lawful, Ethical and Robust. Through our education, Trustworthy AI is explored from different angles in different courses. By having trustworthy AI as a starting point, the Master’s programme gives you a broad knowledge of Artificial Intelligence and deepened knowledge in different subareas of Artificial Intelligence, mainly Social AI, Machine Learning and Data Science.

The Master's programme in AI is set as a collaboration between the Department of Computing Science and the Department of Mathematics and Mathematical Statistics. This allows the students to tailor their education either in computer science profiles such as Social AI or Machine Learning, or advanced statistics in the Data Science profile. All students share a common education in Trustworthy AI.

Practical assignments

During the programme, you will not only learn the theory but also work a lot with your practical skills. The courses on the programme consist of lectures with internationally known researchers, seminars, group work, laboratory work and tutorials in conjunction with different types of assignments. These assignments are usually mandatory and often consist of software development of some kind.

Education close to AI research

All teachers on the programme are active scientists in the AI fields in which they teach, so the students get involved in ongoing research in the broad field of AI. All teaching takes place in English. In some courses, the assignments consist of a student project conducted in collaboration with an organization (industry or public), addressing societal challenges using AI.

Nearly 100 researchers and teachers at Umeå University are involved in areas related to AI. As a student in our program, you can collaborate with AI researchers that are associated with other departments at the university. The diversity of AI research at Umeå University can be seen in the different focus areas of the Center for Transdisciplinary AI (TAIGA).

Education close to AI research

In the Master's programme in Artificial Intelligence students get in involved in ongoing research in the broad field of AI.

Entry requirements

Necessary prerequisites for admission to the programme are theoretical knowledge and practical skills regarding algorithmic problem solving, including well-developed programming skills. This is typically acquired through studies in computer science. In addition, prerequisites include courses in mathematics such as calculus, linear algebra, and a course in either formal logic or mathematical statistics.

Also, fill in a self-evaluation form!

To shorten the time required to assess your application we would appreciate it if you would fill in a self-evaluation form and upload it to your account at universityadmissions.se.

NOTE: The form provides complementary information to your original application. By providing us with additional information about which courses contains the core required courses for the Master in AI, you will assist us in shortening the assessment times. You will still be evaluated solely on the merits provided in your original application.

If you have any questions regarding your application to the Master's programme in AI at Umeå University, please don’t hesitate to contact us.

Two different degrees

Depending on your selected courses in our program you can have one of two different degrees. A degree in Mathematical statistics if you select courses specialized in Data Science; or a degree in Computing Science with specialization in Artificial Intelligence if you select courses specialized in Social AI and Machine Learning. You have large freedom to choose courses depending on interest, although some courses are strongly recommended.

Count on a 40-hour workweek even if there are fewer hours scheduled. At the Master’s level, you are expected to take full responsibility for organizing your study work tasks so that deadlines are met, and so that collaborative work within student projects are manageable within office hours. 

Programme overview

Career opportunities

Artificial intelligence is embedded in our digital tools to make use of the vast amount of data that is collected, for giving additional value tailored to individuals and situations, and for building digital infrastructures for society. Our digital society is rapidly transforming in ways that affect how we work, educate, and entertain ourselves, socialize and engage in society.

Consequently, society is facing a rapidly increasing demand for competence in artificial intelligence that is necessary to push the development in ways that are beneficial to society. Industry’s and public organisations’ demand for expertise in artificial intelligence will increase even more in the foreseeable future.

Develop future digital tools

With the broad and core competence in Artificial Intelligence and the practical skills that the programme will give, you will have great opportunities in different future areas of work. Following your degree, you can pursue a research career or a career as an AI specialist in the industry or the public sector. You will learn how to develop future digital tools based on AI methods and theories. Tools that can for example be applied to improving the environment, health, and education of children or address societal issues such as democracy justice, and safety. It could also be about building software for self-driving cars and other transportation systems. You will be able to develop AI architectures, data management strategies, and support regarding responsible AI.