Statistics and Machine Learning, Master's Programme, 120 credits

A white and blue winding binary code tunnel leading around a corner.

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.

Autumn 2019
Autumn 2020

Statistics and Machine Learning, Master´s Programme

Autumn 2019, Full-time, Linköping

Start

Autumn 2019

Place of study

Linköping

Pace of study

Full-time

Level

Second-cycle

Teaching form

On-Campus

Education language

English

Application code

LIU-91009

Entry requirements

Bachelor's degree equivalent to a Swedish Kandidatexamen within statistics, mathematics, applied mathematics, computer science, engineering or a similar degree. Completed courses with passing grade in following subjects:
- calculus
- linear algebra
- statistics
- programming

English corresponding to the level of English in Swedish upper secondary education (English 6/B). Exemption from Swedish 3.

Special selection

Selection will be based on:

Academic merits and Letter of Intent

Each applicant should therefore enclose a letter of intent written in English, explaining why the applicant wants to study at the programme, how the applicant’s academic background is related to the contents of the programme and how the applicant’s academic background matches to the specific program requirements. If there are courses in the applicant’s transcripts that match to the courses mentioned in the specific requirements, the applicant is recommended to name these courses in the letter of intent. It is also recommended that the applicant includes a description of other relevant experience into the letter of intent (job experience, project participation etc. related to the programme’s specific requirements or to the programme contents).

Degree

Degree of Master of Science (120 Credits) with a major in Statistics

Tuition fees

SEK 190000 - NB: Applies only to students from outside the EU, EEA and Switzerland.

Syllabus and curriculum

Admission requirements Show less

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

Autumn 2020, Full-time, Linköping

Apply

Start

Autumn 2020

Place of study

Linköping

Pace of study

Full-time

Level

Second-cycle

Teaching form

On-Campus

Education language

English

Application code

LIU-91009

Entry requirements

English corresponding to the level of English in Swedish upper secondary education (English 6/B). Exemption from Swedish 3.

Special selection

Selection will be based on:

Academic merits and Letter of Intent

Degree

Degree of Master of Science (120 Credits) with a major in Statistics

Tuition fees

SEK 190000 - NB: Applies only to students from outside the EU, EEA and Switzerland.

Syllabus and curriculum

Admission requirements Show less

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

Autumn 2020, Full-time, Linköping

Start

Autumn 2020

Place of study

Linköping

Pace of study

Full-time

Level

Second-cycle

Teaching form

On-Campus

Education language

English

Application code

LIU-90509

Entry requirements

English corresponding to the level of English in Swedish upper secondary education (English 6/B). Exemption from Swedish 3.

Special selection

Selection will be based on:

Academic merits and Letter of Intent

Degree

Degree of Master of Science (120 Credits) with a major in Statistics

Tuition fees

SEK 190000 - NB: Applies only to students from outside the EU, EEA and Switzerland.

Syllabus and curriculum

Admission requirements Show less

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