Statistics and Machine Learning Linköping University

Award	Attendance	Study	Duration	Start	Domestic fees	International fees
MSc	On-Campus	Full-time	2 years	August	find out	kr190000 total per

Course fee notes

Citizens from countries outside the EU/EEA and Switzerland must pay tuition fees for higher education in Sweden. Exceptions might apply. For detailed information please check www.universityadmissions.se. Higher education studies for citizens of EU/EEA countries and Switzerland are free of charge.

Generally, tuition fees at Linköping University are between SEK 80,000 and 136,000 per academic year.

Tuition fees at Linköping University include the following benefits:

Swedish language courses for beginners
The Swedish state's insurance FAS+, including accident and property cover
An accommodation offer

Course overview

The programme focuses on modern methods from machine learning and database management that use the power of statistics to build efficient models, make reliable predictions and optimal decisions. The programme provides students with unique skills that are among the most valued on the labour market.

The rapid development of information technologies has led to the overwhelming of society with enormous volumes of information generated by large or complex systems. Applications in IT, telecommunications, business, robotics, economics, medicine, and many other fields generate information volumes that challenge professional analysts. Models and algorithms from machine learning, data mining, statistical visualisation, computational statistics and other computer-intensive statistical methods included in the programme are designed to learn from these complex information volumes. These tools are often used to increase the efficiency and productivity of large and complex systems and also to make them smarter and more autonomous. This naturally makes these tools increasingly popular with both governmental agencies and the private sector.

The programme is designed for students who have basic knowledge of mathematics, applied mathematics, statistics and computer science and have a bachelor’s degree in one of these areas, or an engineering degree.

Most of the courses included in the programme provide students with deep theoretical knowledge and practical experience from massive amounts of laboratory work.