For more information about Statistics and Machine Learning at Linköping University, please visit the webpage using the button above.

The award
MSc

How long you will study
2 years

Domestic course fees
find out

How you will study
full-time

Course starts
August

International course fees
find out

All study options

About Statistics and Machine Learning at Linköping University

Data is the driving force behind today's information-based society. There is a rapidly increasing demand for specialists who are able to exploit the new wealth of information in large and complex systems. 

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.

Students will be given the opportunity to learn:

  • how to use classification methods to improve a mobile phone's speech recognition software ability to distinguish vowels in a noisy environment
  • how to improve directed marketing by analysing shopping patterns in supermarkets' scanner databases
  • how to build a spam filter
  • how to provide early warning of a financial crisis by analysing the frequency of crisis-related words in financial media and internet forums
  • how to estimate the effect that new traffic legislation will have on the number of deaths in road accidents
  • how to use a complex DNA microarray dataset to learn about the determinants of cancer
  • how interactive and dynamic graphics can be used to determine the origin of an olive oil sample.

The programme contains a wide variety of courses that students may choose from. Students willing to complement their studies with courses given at other universities have the possibility to participate in exchange studies during the third term. Our partner programmes were carefully selected in order to cover various methodological perspectives and applied areas.

During the final term of the programme, students receive help in finding a private company or a government institution where they can work towards their thesis. There they can apply their knowledge to a real problem and meet people who use advanced data analytics in practice.

Demand is increasing rapidly for specialists able to analyse large and complex systems and databases with the help of modern computer-intensive methods. Business, telecommunications, IT and medicine are just a few examples of areas where our students are in high demand and find advanced analytical positions after graduation.

Students aiming at a scientific career will find the programme the ideal background for future research. Many of the programme''s lecturers are internationally recognised researchers in the fields of statistics, data mining, machine learning, database methodology and computational statistics.

Study options for this course

Notes about fees for this course

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

Entry requirements

Contact Linköping University to find course entry requirements.

Ask a question

Ask Linköping University for more information by completing this form

Desired Start Year

Your question will be sent directly to Linköping University. Your question is subject to the StudyLink terms and conditions. On submitting this form you are consenting to us sharing the information you have supplied with Linköping University inline with the StudyLink privacy policy.

Other courses at Linköping University

There are 28 other courses listed from Linköping University. A selection of these are displayed below:

Location of Linköping University

Linköping University main campus is shown on the map below:

Explore Linköping University

Click the following videos and images to expand or play