Statistics and Machine Learning
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
Į magistro studijų programas gali stoti visi, baigę universitetą arba besimokantys paskutiniame kurse. Studijos kurias baigei ar tebesimokai turi būti panašios krypties kaip ir tos, į kurias nori stoti, kadangi priėmimas yra paremtas ECTS kreditų suderinamumu.
ECTS kreditų išrašas - jei dar nesi baigęs aukštosios mokyklos, būtina prisegti ECTS kreditų išrašą, kuriame būtų matyti, kokius dalykus Tu mokeisi bei kokius pažymius ir kiek kreditų už juos gavai. Kai siunti anketą paskutiniame kurse, diplomą reikia prisegti vėliau, kai tik jį gausi.
Jei dar nesi baigęs aukštosios mokyklos, prie anketos būtinai turi prisegti šį užpildytą dokumentą, patvirtinantį, kad studijuoji ir šiais metais baigsi savo studijas. Dokumentas turi būti patvirtinas universiteto administracijos.
Bakalauro diplomas – jei jau esi baigęs aukštąją mokyklą, išrašo nereikia, užtenka prie anketos prisegti savo Bakalauro diplomą.
Svarbu, jog anglų kalbos testo sertifikatą ir visus kitus reikalingus dokumentus atsiųstum iki balandžio 10d. Anglų kalbos žinias gali patvirtinti vienu iš šių būdų:
IELTS – 6.5 (ne mažiau nei 5.5 iš kiekvienos dalies).
TOEFL - 90. Ne mažiau 20 (iš 30) taškų turi būti surinkta writing dalyje. TOEFL testo rezultatai privalo būti nusiųsti tiesiogiai iš centro, kuriame laikei testą.
Išimtis! Asmenims, turintiems brandos atestatą, kuriame nurodytas anglų kalbos B2 lygis anglų kalbos testo laikyti nereikia
- Bachelor's degree 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
- Selection will be based on academic merits. Each applicant is encouraged to submit a Letter of Intent in order to provide us with more information about their qualifications and how they will contribute to/benefit from the programme. If applicants hold a degree that does not include a bachelor’s essay or project, their Letter of Intent should describe previous studies and any academic activities that are related to the master’s programme or the programmes applied for.
Note. You must provide your Bachelor's degree syllabus to prove you have required credits in particular subjects.
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 statistic.
