MSc Statistics and Data Mining, 120 credits
Degree: Master of Science with a major in Statistics.
There is a rapidly increasing demand for specialists who are able to exploit the new wealth of information in large and complex datasets to improve analysis, prediction and decision making. The programme focuses on modern developments in the intersection of statistics, artificial intelligence and database management, providing the participants with unique competence in the labour market.
With the growth of computer capabilities, databases are growing larger and become more complex, making traditional statistical methods less effective or even unsuitable. Data from economic transactions, individual health records, internet search, and environmental data are just a few examples of the content of enormous databases awaiting thorough examination.
In these data-rich environments, methods from data mining, statistical visualization, computational statistics and other computer-intensive statistical methods included in the programme have become increasingly popular for both governmental agencies and the private sector.
Our programme is designed for those students that retain basic knowledge of mathematics, statistics and computer science and have a bachelor degree in one of these areas.
Students who have finished the bachelor’s programme Statistics and Data Analysis (Statistik och dataanalys) at LiU will find our master’s programme to be the natural continuation of their studies where they can learn more about advanced data (including text) mining methods, databases, web programming and survey sampling, study Bayesian methods, learning systems in bioinformatics and many other interesting subjects.
Students will be given an 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 courses in Data Mining and Statistical Learning, Data mining: clustering and association analysis, Visualization and Bayesian learning constitute the core of the programme. In addition, master’s students have the freedom to choose complementary courses depending on their background and interest. The set of complementary courses includes Computational Statistics, Database Technology, Health Statistics, Optimization, Web programming, a course in Text Mining and other courses covering different data analysis methods and application areas. Students in computer science with limited previous exposure to statistics are invited to a basic preparatory course in statistical theory.
While students write their master’s thesis we help them finding a private company or governmental institution where they can apply their knowledge to a real problem and meet people who work mainly with advanced data analysis.
Employment and career opportunities
There is a rapidly increasing demand for specialists able to analyse large and complex systems and databases with 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?
Our master’s degree opens up the opportunity to obtain high-profile jobs as senior data analysts or other advanced positions in private companies or governmental institutions in, for example, the technological, financial or medical sector.
Compared to the bachelor’s degree of the same subject, our master’s degree provides the opportunity to work with the development of methods and search for senior positions or jobs with a more analytical profile.
Students aiming for a scientific career will also find the programme an ideal background for future research. Many of the programme's lecturers are internationally established researchers in the fields of data mining, database methodology and computational statistics.
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. Undergraduate courses in basic 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 applied for.
All supporting documents, including the Letter of Intent and the specific paper, should be sent to University Admissions in Sweden, FE 1, SE-833 83 Stroemsund, Sweden.
Application period opens october 2013
Go to universityadmissions.se
Tuition fees 2013/2014
- Citizens from within the EU/EEA and Switzerland: No tuition fees
- All others: 95,000 SEK (approx. USD14,000/10,400 Euro) per academic year
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Last updated: 2013-01-16