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.
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?" How? In layman's terms, the relationship between the data and the predictions/patterns is learnt by examining lots of relevant example data. This simple idea has become central to the design of search engines, robots, and sensor systems and the processing of large data sets.
Career prospects
The demand for engineers and scientists with knowledge in Machine Learning is growing as the amount of data in the world grows. Machine Learning is widely used in applications where sensor data is processed – automatic speech processing, computer vision or radar signal processing – and in areas where information is retrieved from large amounts of data. Internet search is the most obvious of this latter application. But large datasets occur in many domains, such as Economics, Medicine, Meterology, Geoscience, and Astronomy. The fields of Computer Vision, Speech Technology, and Information Retrieval also exploit ideas from machine learning and KTH has research groups in these areas.
This Master's programme is a suitable basis for work in a research and development department in industry as well as for a continued research career in any of these areas.
Programme outline
In this programme you will learn the mathematical and statistical foundations and methods for Machine Learning and become comfortable manipulating them to solve questions. You will also gain practical experience of how to match, apply and implement relevant techniques from the field to real world problems. Therefore, the programme provides the students with both the theoretical tools and hands-on know how of machine learning and this is an excellent basis for eithera career within industry or further advanced studies.
The first semester is devoted to compulsory courses giving an introduction to the field. Then students can focus on one of three tracks:
- Perception and Cognition
- Information Retrieval
- Computational Biology
The final semester is dedicated to a degree project.
Degree project
A part of the second year is dedicated to a degree project of 30 ECTS credits. The purpose of the degree project is for the student to demonstrate the ability to perform independent project work, using the skills obtained from the courses in the programme.
