Signal Processing and Machine Learning - Specialization
Signal Processing and Machine Learning
This specialization is aimed at students who are interested in acoustic signal processing, data science, audio, sound field analysis, hearing, speech and music recognition. The courses selected in this specialization provide competences in audio signal processing, machine learning, spatial sound, signal analysis and computational methods in acoustics. These competences prepare you to work in multiple areas, including tech companies, audio industry, communication technology, consumer electronics, information technology and research.
The following 5 ECTS are mandatory for the specialization:
| 02471 | Machine learning for signal processing | 5 | point | Autumn E1B (Thurs 13-17) |
It is mandatory to select a minimum of 10 ECTS of the courses below:
| 22003 | Auditory signal processing and perception | 10 | point | Spring F1 (Mon 8-12, Thurs 13-17) |
| 34860 | Advanced acoustics | 10 | point | Spring F2 (Mon 13-17, Thurs 8-12) |
Select a minimum of 10 ECTS of the courses below:
| 34865 | Numerical acoustics | 5 | point | Spring F3A (Tues 8-12) |
| 34867 | Acoustic conditions at the Roskilde Festival | 5 | point | Outside schedule structure |
| 34870 | Electroacoustic transducers and systems | 10 | point | Autumn E2 (Mon 13-17, Thurs 8-12) |
| 34880 | Structure-borne sound | 10 | point | Autumn E4 (Tues 13-17, Fri 8-12) |
And/or the electives:
| 02450 | Introduction to Machine Learning and Data Mining | 5 | point | Spring F4A (Tues 13-17), Autumn E4A (Tues 13-17) |
| 02456 | Deep learning | 5 | point | Autumn E2A (Mon 13-17) |
Specializations are merely recommended ways of choosing the courses in the curriculum. Applicants are not admitted to a specialization but to the programme and it is possible to choose among all the courses in the curriculum following the directions given. However, if a specialization has been fulfilled the title of the specialization may be added to the diploma.