Artificial Intelligence, 20 cr
Type of the study module
Advanced Studies
Contact
Tapio Elomaa, Heikki Huttunen
Learning Outcomes
| - | Student is able to study state-of-the-art in machine learning and signal processing methods and can adopt and adapt these techniques, especially in the robotics application domain. Student is able to design, train and deploy a machine learning model for classification and regression. This module will provide expert-level knowledge on artificial intelligence technologies needed in industry and consumer applications.
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Prerequisites
At least the following courses are prerequisites for the major: TIE-02207 Programming 2: Basics, ASE-9306 Introduction to Robotics and Automation and ASE-1258 Introduction to Control. ( Advisable )
Content
Compulsory courses
| Course | Credit points | Class |
| SGN-41007 Pattern Recognition and Machine Learning | 5 cr | IV |
| SGN-44006 Artificial Intelligence | 5 cr | IV |
| Total | 10 cr |
Complementary Courses
Select at least 10 credits from the following list of courses. The student may also propose courses outside this list to the responsible professors.
Please select at least 10 credits of courses
| Course | Credit points | Additional information |
| MAT-61706 Bayesian Filtering and Smoothing | 5 cr | |
| SGN-26006 Advanced Signal Processing Laboratory | 5 cr | 1 |
| SGN-33007 Media Analysis | 5 cr | |
| SGN-43006 Knowledge Mining and Big Data | 5 cr | |
| SGN-45007 Computer Vision | 5 cr | |
| SGN-81006 Signal Processing Innovation Project | 5-8 cr | 1 |
| TIE-22307 Data-Intensive Programming | 5 cr |
1. Only one of the two laboratory courses (SGN-26006 and SGN-81006) may be taken.
Additional information
Opintokokonaisuus on tarkoitettu syventäväksi lisäkokonaisuudeksi Robotics and AI -pääaineen opiskelijoille, eikä sitä voi suorittaa erillisenä tästä pääaineesta.
The study module is intended to extend the Robotics major to Robotics and AI major of 50 cr. This module can only be taken together with the Robotics major.