MSc Statistics and Data Mining

Linköping University

Program Description

MSc Statistics and Data Mining

Linköping University

MSc Statistics and Data Mining, 120 credits

There is a rapidly increasing demand for specialists who are able to exploit the new wealth of information in large and complex databases to improve analysis, prediction and decision making. The programme focuses on modern developments in the intersection of statistics, machine learning, artificial intelligence and database management, providing students with a unique competence in the labour market.

With the growth of computer capabilities, databases become larger and more complex, making traditional statistical methods less effective or even unsuitable. Data from economic transactions, individual health records, internet search, and telecommunications are just a few examples of the content of enormous databases that challenge professional analysts. In these data-rich environments, methods from data mining, machine learning, statistical visualisation, computational statistics and other computer-intensive statistical methods included in the programme have become increasingly popular for 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 degree in one of these areas, or an engineering degree.

Students who have finished the bachelor’s programme Statistics and Data Analysis (Statistik och dataanalys) at Linköping University will find our master’s programme to be the natural continuation of their studies where they can learn more about various data analysis and machine learning methods, including Bayesian methods, text mining and statistical methods in bioinformatics.

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 an early signal of a financial crisis by analysing the frequency of crisis-related words in financial media and internet forums
  • how to estimate the effect that a new legislation on traffic has on the number of deaths
  • how to use a complex DNA micro array dataset to learn about the determinants of cancer
  • how interactive and dynamic graphics can be used to determine the origin of an olive oil.

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 do exchange studies during the third semester. Our partner programmes were carefully selected in order to cover various methodological perspectives and applied areas.

During the final semester of their studies, students receive help in finding a private company or a governmental institution where they can write their theses. There they can apply their knowledge to a real problem and meet people who use advanced data analysis in practice.

Career opportunities

There is a rapidly increasing demand for specialists able to analyse large and complex systems and databases with the help of modern computer-intensive methods. Do you know for example that Barack Obama’s administration was looking for Data Mining analysts for the elections in 2012?

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.

Compared to the bachelor’s degree of the same subject, the master’s programme provides the opportunity to work with the development of methods and to search for senior positions or jobs with a more analytical profile.

Students aiming at a scientific career will also find the programme an 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.

Programme facts

  • Degree: Master of Science (120 credits) in Statistics
  • Language: English
  • Duration: Two years
  • Pace of study: Full-time
  • Campus: Linköping
  • Application code: LIU-91009
  • Application period: 16 Oct - 15 Jan
  • Start date: August / September

Tuition fees

Citizens from within the EU/EEA and Switzerland: No tuition fees

All others: SEK 95,000 (approx. USD 14,000/EUR 10,400) per academic year

Programme specific requirements

A bachelor’s degree with at least 90 credits, i.e. 18 months of full-time study, in mathematics, applied mathematics, statistics or computer science. The undergraduate courses in mathematics should include both calculus and linear algebra. Basic undergraduate courses in statistics and computer science are also required.

Each applicant must enclose a letter of intent written in English, explaining why they want to study this programme, and a summary of their bachelor's essay or project. If applicants hold a degree that does not include a bachelor's essay or project, then their letter of intent should describe previous studies and any other academic activities related to the master's programme.

All supporting documents, including the letter of intent and the specific paper, should be sent to University Admissions in Sweden, FE 1, SE–838 73 Frösön, Sweden.

This school offers programs in:
  • English


Last updated June 8, 2016
Duration & Price
This course is Campus based
Start Date
Start date
Aug. 2017
Duration
Duration
2 years
Full time
Price
Price
95,000 SEK
Information
Deadline
Jan. 15, 2017
Late applications might be considered.
Start date Aug. 2017
Place
Sweden Linköping
Application deadline Jan. 15, 2017
Late applications might be considered.
End date Request Info
Duration 2 years
Price 95,000 SEK
All others ( per academic year ) ; Citizens from within the EU/EEA and Switzerland: No tuition fees
Videos

Statistics and Data Mining at Linköping University