Program Overview

Introduction to Machine Learning

Machine Learning develops algorithms to find patterns or make predictions from empirical data. This master's programme will teach students to master these skills. Machine Learning is increasingly used by many professions and industries such as manufacturing, retail, medicine, finance, robotics, telecommunications, and social media. Graduates from the programme will be experts in the field, qualified for exciting careers in industry or doctoral studies.

Application Deadlines

• Application opens: 16 October 2025
• Last day to apply: 15 January
• Submit documents and, if required, pay application fee: 2 February
• Admission results announced: 26 March

Machine Learning at KTH

In this programme, students will learn the mathematical and statistical foundations and methods for machine learning with the goal of modelling and discovering patterns from observations. They will also gain practical experience in matching, applying, and implementing relevant machine learning techniques to solve real-world problems in a broad range of application domains. Upon graduation from the programme, students will have gained the confidence and experience to propose tractable solutions to potentially non-standard learning problems which they can implement efficiently and robustly.

Programme Structure

The programme starts with mandatory courses in machine learning and artificial intelligence to provide an introduction to the field and a solid foundation. These courses are followed by an advanced course in machine learning and research methodology. From the second semester, students choose courses from two areas: application domains exploiting machine learning and theoretical machine learning. These areas correspond to the core competencies of a machine learning expert.

Courses in the Programme

The courses in the programme cover topics such as:

• Machine learning
• Deep learning
• Statistical modelling
• Artificial intelligence
• Computer vision
• Speech technology
• Information retrieval
• Optimisation

Future and Career

The demand for engineers and scientists with expertise in Machine Learning is growing, driven by the increased availability of data, the increasingly powerful ML models, and their applicability across a wide range of domains and industries. After graduation, students can pursue a career in industry, at a start-up or in a traditional, well-established company. Graduates work as software developers, deep learning engineers, computer vision engineers, data analysts, software engineers, quantitative analysts, data scientists, and systems engineers.

Sustainable Development

Graduates from KTH have the knowledge and tools for moving society in a more sustainable direction, as sustainable development is an integral part of all programmes. The three key sustainable development goals addressed by the master's programme in Machine Learning are:

• Good Health and Well-being
• Sustainable Cities and Communities
• Peace and Justice Strong Institutions

Programme Details

• Duration: Two years (120 ECTS credits)
• Language: English
• Degree: Master of Science
• Location: KTH Campus in Stockholm, given by the School of Electrical Engineering and Computer Science (at KTH)