Machine Learning, 25 cr
Type of the study module
Intermediate Studies
Contact
Heikki Huttunen, Joni Kämäräinen
Learning Outcomes
| - | Opiskelija kykenee löytämään syvällisempiä menetelmiä kirjallisuudesta sekä muokkaamaan niitä käsillä olevaan ongelmaan sopivaksi.
Student is able to find more advanced methods and adapt them to to solve the problem at hand. |
| - | Opiskelija osaa käyttää Matlabia hahmontunnistusongelman laskennalliseen ratkaisemiseen.
The student can use Matlab for computational solution of a machine learning problem. |
| - | Opiskelija osaa käyttää Pythonin kirjastoja hahmontunnistusongelman laskennalliseen ratkaisemiseen.
The student can use Python libraries for computational solution of a machine learning problem. |
| - | Opiskelija osaa ratkaista yksinkertaisen hahmontunnistusongelman.
Student can solve basic pattern recognition problem. |
| - | Opiskelija osaa soveltaa hahmontunnistusosaamistaan audion, kuvan tai robotiikan sovellusalueilla.
The student can apply the pattern recognition skills for audio, images or robotics. |
Prerequisites
Passing the module requires programming skills and understanding of the basic engineering mathematics. ( Advisable )
Further Opportunities
| Study block | Credit points |
| Robotics | 30 cr |
Content
Compulsory courses
| Course | Credit points | Additional information | Class |
| SGN-11000 Signaalinkäsittelyn perusteet | 5 cr | 1 | II |
| SGN-13006 Introduction to Pattern Recognition and Machine Learning | 5 cr | III | |
| SGN-41007 Pattern Recognition and Machine Learning | 5 cr | III | |
| Total | 15 cr |
1. Kurssi vaihtoehtoinen kurssin SGN-11007 kanssa.
Student may select either SGN-11000 (Finnish) or SGN-11007 (English).
Optional Compulsory Courses
SGN-80000 Signaalinkäsittelyn kandidaattiseminaari on pakollinen, mikäli kokonaisuuteen tehdään kandidaatintyö. SGN-80000 is compulsory only to those students who have Signal processing as their major in their B.Sc. degree.
| Course | Credit points | Class |
| SGN-80000 Signaalinkäsittelyn kandidaattiseminaari | 0 cr | III |
Complementary Courses
Students of international BSc program take at least 5 cr from the list.
Should be completed to the minimum study module extent of 25 ETCS
| Course | Credit points | Additional information | Class |
| ASE-7410 Kuvaan perustuvat mittaukset | 5 cr | III | |
| MAT-02550 Tilastomatematiikka | 4 cr | II | |
| MEI-56606 Machine Vision | 5 cr | III | |
| SGN-12001 Johdatus kuvan- ja videonkäsittelyyn | 5 cr | III | |
| SGN-14007 Introduction to Audio Processing | 5 cr | III | |
| TIE-20100 Tietorakenteet ja algoritmit | 5 cr | 2 | II |
1. The course SGN-12007 in English is an alternative to SGN-12001.
2. The course TIE-20106 in English is an alternative to TIE-20100.
Additional information
Machine learning is the central concept in the modern information technology and will play a predominant role in digitalization of the society. Its applications are vast varying from computer vision systems, audio and speech processing applications to robotics and human-robot interaction. Another emerging field is big data which means that machine learning algorithms and pattern recognition are applied to large datasets from finance, security and safety, health and biotechnology, Internet content etc. This module provides the students strong practical knowledge and expertise on the main approaches and methodologies of machine learning and pattern recognition. Moreover, the students will have hands-on experience on the most emerging applications of machine learning: computer vision, audio and speech processing and big data.