Master's programme in Machine Learning

Machine Learning is a scientific discipline focused on the development of algorithms that spot patterns or make predictions from empirical data. Today's demand for expertise in machine learning far exceeds the supply, and this imbalance will become more severe over the coming decade. The programme equips you for an international career and will also prepare you for further studies at PhD-level.

Application closed

The application for the programme is now closed. Opens again 16 October 2017.

16 October 2017: Application opens
15 January 2018: Application deadline

Non-EU/EEA/Swiss citizens: The full programme tuition fee is SEK 310,000
Non-EU/EEA/Swiss citizens are generally required to pay an application fee of SEK 900.

EU/EEA/Swiss citizens: There are no tuition fees for EU/EEA/Swiss citizens
EU/EEA/Swiss citizens are not required to pay an application fee.

Read more about tuition and application fees

Degree awarded: Master of Science
Language of instruction: English
Duration: Two years (120 ECTS credits)
Programme start: Late August
Location: KTH Campus, Stockholm
School: School of Computer Science and Communication (at KTH)

For questions regarding programme content and specific admission requirements, feel free to contact the programme coordinators.

Programme coordinator team:

Already such algorithms have allowed computers to answer these questions: "Where are the faces in this photo?" and "Can you recommend a movie for me to watch?" In layman's terms, the relationship between data and predictions/patterns is learnt by examining a large quantity of relevant example information. This idea has become central to the design of search engines, robots and sensor systems which process large data sets.

Machine Learning at KTH

In this programme you will learn the mathematical and statistical foundations and methods for Machine Learning with the goal of modelling and discovering patterns from real world observations. You will also gain practical experience of how to match, apply and implement relevant techniques from the field to real world problems in a vast range of application domains.

The programme starts with compulsory courses in machine learning, artificial intelligence, computer security, an advanced course in machine learning and research methodology which provides an introduction and solid foundation to the field. From the second term the students choose courses from three areas; application domains within machine learning, applied mathematics/statistics, and computer science.

The first area describes how machine learning is used to solve problems in particular application domains such as computer vision, information retrieval, speech and language processing, computational biology and robotics. The second area gives the students the chance to take more basic theoretical courses in applied mathematics, statistics, and machine learning.The third area allows the students to deepen their knowledge in theoretical computer science and programming languages.

The programme also consist of 30 ECTS credits of elective courses which you can choose from a wide range of courses to specialise further in your field of interest or broaden to new areas within machine learning.

The final term is dedicated to a degree project which involves participating in advanced research or design projects in an academic or industrial environment, in Sweden or abroad. The purpose of this project is for the student to demonstrate the ability to perform independent project work, using the skills obtained from the courses in the programme.



The demand for engineers and scientists with knowledge in Machine Learning is growing as the amount of data in the world increases. After graduation you can pursue careers, for example as a software developer, deep learning engineer, computer vision engineer, data analyst, software engineer, quantitative analyst, data scientist, and systems engineer for companies as Dice, Logitech, Google, and McKinsey in for example Sweden, Switzerland, Germany, China, India, and the US.

This master's programme is also a suitable basis for work in a research and development department in industry, as well as for a continued research career, and doctoral studies.


Find out what students from the programme think about their time at KTH.

Deepa Krishnamurthy, India

"KTH provides an international platform where the students are exposed to a myriad of opportunities."

Meet the students

Changes in the programme may occur.

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