In this Machine Learning programme at KTH Royal Institute of Technology, you will learn the mathematical and statistical foundations and methods for machine learning with the goal of modelling and discovering patterns from observations. You will also gain practical experience of how to match, apply and implement relevant machine learning techniques to solve real-world problems in a broad range of application domains.
Upon graduation from the programme, you will have gained the confidence and experience to propose tractable solutions to potentially non-standard learning problems which you can implement efficiently and robustly. Stockholm has both a vibrant start-up community and large established companies integrating AI and Machine Learning into their technological development. This gives you the potential for relevant and exciting industrial work within the field during and after your studies.
To provide an introduction to the field and a solid foundation the programme starts with compulsory courses in machine learning and artificial intelligence. These courses are followed by an advanced course in machine learning and research methodology. From the second semester, students choose courses from within two areas: application domains exploiting machine learning and theoretical machine learning. These areas correspond to the core competencies of a machine learning expert.
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 a career in industry, at a start-up or in a traditional well-established company. Possible titles are software developer, deep learning engineer, computer vision engineer, data analyst, software engineer, quantitative analyst, data scientist, and systems engineer in companies such 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.
Programme StructureCourses include:
- Philosophy of Science and Research Methodology
- Program Integrating Course in Machine Learning
- Artificial Intelligence
- Machine Learning
- Machine Learning, Advanced Course
- Advanced Individual Course in Computational Biology
- Research project in Robotics, Perception and Learning
- 24 months
Start dates & application deadlines
- Apply before
DisciplinesRobotics Computer Sciences Machine Learning View 13 other Masters in Robotics in Sweden
We are not aware of any academic requirements for this programme.
A Bachelor’s degree, or equivalent, corresponding to 180 ECTS credits, with a level in Mathematics and Computer Science equal to, or higher than, that of the following courses at KTH:
- SF1624 Algebra and geometry
- SF1625 Calculus in one variable
- SF1626 Calculus in several variables
- SF1924 Probability Theory and Statistics
- DD1337 Programming
- DD1338 Algorithms and Data Structures.
International14505 EUR/yearTuition FeeBased on the tuition of 29011 EUR for the full programme during 24 months.
EU/EEAFreeTuition FeeBased on the tuition of 0 EUR for the full programme during 24 months.
- The full programme tuition fee for non-EU/EEA/Swiss citizens studying this programme is SEK 310,000.
Studyportals Tip: Students can search online for independent or external scholarships that can help fund their studies. Check the scholarships to see whether you are eligible to apply. Many scholarships are either merit-based or needs-based.
Apply and win up to €10000 to cover your tuition fees.