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  • Study Type

    Full time available

  • Subject Areas

    Mathematics

  • Start Date

    August

  • Course Duration

    Two years

  • Course Type

    MSc

  • Course Fees

    Citizens from within the EU/EEA and Switzerland: No tuition fees All others: 190,000 SEK (approx. 22,500 USD/ 19,000 Euro)

  • Last Updated

    30 October 2019

Unleash the power of data and statistics to make the right decisions happen. We integrate statistical modelling and analysis with machine learning, data mining and data management to give you unique skills.

The rapid development of information technologies has overwhelmed society with enormous volumes of information generated by large or complex systems from telecommunications, robotics, medicine, business and many other fields. This master’s programme meets the challenges of learning from these complex volumes by means of models and algorithms from machine learning, data mining and other computer-intensive statistical methods. By joining us, you will increase the efficiency and productivity of the systems and make them smarter and more autonomous.

Learn to make reliable predictions

The programme focusses on modern methods from machine learning and database management that use the power of statistics to build efficient models and make reliable predictions and optimal decisions. You will gain deep theoretical knowledge as well as practical experience from extensive amounts of laboratory work. If you want to complement your studies with courses at other universities, you can participate in exchange studies during the third semester.

Depending on your interests, you will work towards your thesis at a company, a governmental institution or a research unit at LiU. There you can apply your knowledge to a real problem and meet people who use advanced data analytics in practice or you can go deeper into the research.

This programme is for you if you aspire to learn how to:

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

Visit the Statistics and Machine Learning page on the Linköping University website for more details!

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