Data Engineering and Machine Learning, 55 cr

Type of the study module

Advanced Studies

Contact

Heikki Huttunen, Joni Kämäräinen

Learning Outcomes

- 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 design and use modern database systems.
- 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.

Content

Compulsory courses

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

Course Credit points Class
SGN-11007 Introduction to Signal Processing 5 cr IV  
SGN-12007 Introduction to Image and Video Processing 5 cr IV  
SGN-13006 Introduction to Pattern Recognition and Machine Learning 5 cr IV  
SGN-14007 Introduction to Audio Processing 5 cr IV  
SGN-24007 Advanced Audio Processing 5 cr IV  
SGN-26006 Advanced Signal Processing Laboratory 5 cr V  
SGN-33007 Media Analysis 5 cr V  
SGN-41007 Pattern Recognition and Machine Learning 5 cr IV  
SGN-43006 Knowledge Mining and Big Data 5 cr IV  
TIE-20106 Data Structures and Algorithms 5 cr IV  
TIE-22307 Data-Intensive Programming 5 cr V  
Total 55 cr  

Additional information

Data engineering is the emerging field of ICT that requires understanding of the fundamental technologies of machine learning, its most important application fields in vision, audio, signal and data processing and robotics, and understanding of computational and programming solutions to cope with large scale machine learning and data mining problems.

Updated by: Viitala Anna-Mari, 15.03.2019