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Statistics and Machine Learning, Master's Programme

120 credits

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.

Statistics and Machine Learning, Master´s Programme - First and main admission round

Autumn 2024 / Full-time / Linköping

Closed for late application

Statistics and Machine Learning, Master´s Programme - Second admission round (open only for Swedish/EU students)

Autumn 2024 / Full-time / Linköping

Closed for late application

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 computer-intensive statistical methods, machine learning and data mining. 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 focuses 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 research problems.

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

  • estimate the quality of models and make predictions about future unemployment
  • 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

Syllabus and course details

The programme runs over two years and encompasses 120 credits, including a master thesis.

The introductory block of courses in the first semester contains a mix of well-needed courses in statistics, machine learning and programming for the continuation of the programme. The courses Statistical Methods, Machine learning, Computational Statistics, Advanced Data Mining, Deep Learning, Big Data Analytics, and Bayesian learning constitute the core of statistics and machine learning at the programme.

In addition, during the third semester, master’s students have the freedom to choose among several profile courses - aimed to strengthen students’ statistical and analytical competence - and complementary courses - that allow students to focus on applied areas or relevant courses from other disciplines. Opportunities for exchange studies are also provided during the third semester of the programme.

To be awarded the master’s degree, students must pass 90 ECTS credits of courses and successfully defend a master’s thesis of 30 ECTS credits.

Further information

A detailed syllabus, curriculum, and information on the courses you may take can be found in our study information database via the link below. Entry requirements and tuition information can be found by selecting the drop-down ”Admission requirements” available under the Autumn 2024 tab.
Syllabus and curriculum

Career opportunities

A specialist in high demand

Demand is increasing rapidly for specialists able to analyse all kinds of data from small to large and complex systems and databases with the help of modern, computer-intensive, statistical 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 recognized researchers in the fields of statistics, machine learning, data mining, database methodology and computational statistics.

Alumni insights

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Alejandro – alumn from Statistics and Machine Learning

“What I really liked about studying here is that the courses were very practical, we learnt a lot by doing it ourselves which I really enjoyed. Moreover, the student life in Linköping is truly unique”, says former student Alejandro from Spain.
Josh Hyungym Kim, alumn from the master programme in Statistics and Machine Learning

Josh - alumn in Statistics and Machine Learning

This programme has a great balance between theoretical background and practical implementation says former student Josh from Korea.

Student testimonials

Thumbnail Connor Bryce Turner

Connor

What are the main advantages of Master’s programme in Statistics and Machine Learning, and why should you apply? Current student Connor Bryce Turner tells you in this video.

Meet MArtynas, student at Statistics and Machine Learning

Martynas

Martynas Lukosevicius tells you why he chose Linköping University, and what he likes best about the Statistics and Machine Learning Master’s programme.

Meet Shashi, student at Statistics and Machine Learning

Shashi

Why did Shashi Nagarajan choose to study this programme and what are the most interesting subjects? He also tells you what he sees as the best thing about Linköping University.

News

Meet Akshay, student at Statistics and Machine Learning

Master's student awarded for research on traffic flow patterns

Akshay Gurudath receives the Christer Gilén Scholarship for his degree project in statistics and machine learning. In his thesis, Akshay presents and compares models he has built to predict positions of pedestrians, cyclists, and autonomous vehicles.

Measuring muscle mass with neural network

Alexander Karlsson has been awarded the Christer Gilén Scholarship for 2020 in statistics and machine learning for a master’s thesis in which he uses a neural network to improve a method of measuring muscle mass.

Research

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The Division of Statistics and Machine Learning (STIMA)

The STIMA division is part of the Department of Computer and Information Science. The research and teaching activities are focused on modern data analysis and the division hosts the international master's programme in Statistics and Machine Learning.

Application & admission

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How to apply for master's degree studies at LiU

A step-by-step guide to everything you need to know about applying for LiU's international master's degree programmes using the application system in Sweden.

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