Linkping University

Statistics and Machine Learning, M.Sc.

  • Application Deadline
  • 24 months
    Duration
  • Tuition Fee
    9895.5 EUR/year
    Tuition fee
    Free
    Tuition fee
  • English
    Language
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. ThisStatistics and Machine Learning programme is offered byLinkping University.

About

The Statistics and Machine Learning 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 Linköping University's 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.

Career opportunities

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.

Programme Structure

Courses Included

  • Statistical methods
  • Advanced R programming
  • Advanced Academic studies
  • Introduction to Machine Learning
  • Advanced Data Mining
  • Big Data Analytics
  • Introduction to Python
  • Philosophy of Science
  • Bayesian Learning
  • Computational statistics
  • Time series analysis
  • Multivariate Statistical Methods
  • Web Programming
  • Neural networks and learning systems
  • Visualization
  • Advanced Machine Learning
  • Probability Theory
  • Decision Theory
  • Data Mining Project
  • Text mining
  • Database Technology
  • Master's thesis

Detailed Programme Facts

English Language Requirements

You only need to take one of these language tests:

  • Minimum required score:

    6.5

    The IELTS – or the International English Language Test System – tests your English-language abilities (writing, listening, speaking, and reading) on a scale of 1.00–9.00. The minimum IELTS score requirement refers to which Overall Band Score you received, which is your combined average score. Read more about IELTS.

    Take IELTS test
  • Minimum required score:

    575

    The TOEFL – or Test OF English as a Foreign Language – offers a paper-based test (PBT). The final, overall PBT score ranges between 310 and 677, and is based on an average taken from the three test components (listening, structure, and reading). The writing part of this test is scored separately on a scale of 0-6. Read more about TOEFL (PBT).

  • Minimum required score:

    90

    The TOEFL – or Test Of English as a Foreign Language – offers an internet-based test (iBT). The final, overall iBT score ranges between 0 and 120, and includes a scaled average from the four components (reading, listening, speaking, and writing). Read more about TOEFL (iBT).

Academic Requirements

  • Bachelor's degree equivalent to a Swedish Kandidatexamenwithinstatistics, mathematics, applied mathematics, computer sicence, engineering or a similar degree. Courses in calculus and linear algebra, statistics and programming are also required.
  • English corresponding to the level of English in Swedish upper secondary education (English 6/B).

Tuition Fee

  • International

    9895.5 EUR/year
    Tuition Fee
    Based on the original amount of 19791 EUR for the full programme and a duration of 24 months.
  • EU/EEA

    Free
    Tuition Fee
    Based on the original amount of 0 EUR for the full programme and a duration of 24 months.
  • 190000 kr

Funding

Check the programme website for information about funding options.

StudyPortals Tip: Students can search online for independent or external scholarships that can help fund their studies. Check the scholarships to see whether you are eligible to apply. Many scholarships are either merit-based or needs-based.

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