Data Engineering and Machine Learning, 55 op
Opintokokonaisuuden tyyppi
Advanced Studies
Yhteyshenkilö
Ioan Tabus, Joni Kämäräinen, Heikki Huttunen
Osaamistavoitteet
| - | Student can solve basic and advanced pattern recognition problems. |
| - | Student is able to find more advanced methods and adapt them to to solve the problem at hand. |
| - | The student can apply the pattern recognition skills for audio, images or robotics. |
| - | The student can implement data engineering pipelines that integrate with other information systems. |
| - | The student can use Matlab for computational solution of a machine learning problem. |
| - | The student can use Python libraries for computational solution of a machine learning problem. |
Sisältö
Pakolliset opintojaksot
Recommeded years of study are marked below from the MSc study phase point of view, i.e., 4 = 1st year of MSc study phase, 5 = 2nd year of MSc study phase. The students are encouraged to contact the responsible persons of this study module if they wish to make changes to their study structure. This study module assumes strong programming background during BSc studies and therefore students are encouraged to include the following courses to their study plan: TIE-02207 Programming 2: Basics and TIE-02408 Programming 3: Techniques
| Opintojakso | Opintopisteet | Vuosikurssi |
| SGN-11007 Introduction to Signal Processing | 5 op | IV |
| SGN-12007 Introduction to Image and Video Processing | 5 op | IV |
| SGN-13006 Introduction to Pattern Recognition and Machine Learning | 5 op | IV |
| SGN-14007 Introduction to Audio Processing | 5 op | IV |
| SGN-24007 Advanced Audio Processing | 5 op | IV |
| SGN-26006 Advanced Signal Processing Laboratory | 5 op | V |
| SGN-33007 Media Analysis | 5 op | V |
| SGN-41007 Pattern Recognition and Machine Learning | 5 op | IV |
| SGN-44006 Artificial Intelligence | 5 op | IV |
| TIE-20106 Data Structures and Algorithms | 5 op | IV |
| TIE-22307 Data-Intensive Programming | 5 op | V |
| Yhteensä | 55 op |
Lisätiedot
Data engineering is the emerging field of information technology and computer science that requires understanding of the fundamental technologies of machine learning. The most important fields of data engineering are computer vision, audio, signal and data processing and robotics. Moreover, in-depth knowledge on how to implement machine learning and data analysis systems is at the core of this module.