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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 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 large 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.

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

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. Of particular interest to many will be the chance to learn about and understand in detail the exciting field of deep learning through several state-of-the-art courses such as:

The programme also has 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 extend your knowledge 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. With this project, student gets to demonstrate their ability to perform independent project work, using the skills obtained from the courses in the programme. In the past students from the programme have completed projects at companies such as Saab, Elekta, Flir, Eriksson, Tobii, Spotify, Thales, Huawei.

This is a two year programme (120 ECTS credits) given in English. Graduates are awarded the degree of Master of Science. The programme is given mainly at KTH Campus in Stockholm by the School of Electrical Engineering and Computer Science (at KTH).

Topics covered

Machine learning, deep learning, statistical modelling, artificial intelligence, computer vision, speech technology, information retrieval, optimization.

Specific requirements for the master’s programme in Machine Learning

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
SF1901 Probability theory and statistics
DD1337 Programming
DD1338 Algorithms and Data Structures

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