Signal Processing and Machine Learning is a Master of Science (Technology) specialisation at Tampere University. It covers signal processing theory and algorithms, deep learning and neural networks, audio and speech processing, imaging and computer vision, and statistical modelling and data analysis. The content combines theory and practice, with teaching in both classical signal processing and machine learning methods for classification, regression, unsupervised learning and reinforcement learning.
The programme comprises 120 ECTS credits. Students complete 90 ECTS of courses and 30 ECTS for the master’s thesis. The studies usually take two years, with three semesters for courses and one semester for the thesis. Tampere University says students can choose elective studies and supplementary courses, or focus on imaging, machine hearing and vision, or signal processing and data analysis. The programme is research-driven and aims to integrate students into research groups.
Graduates are described as eligible for work in research, design, development, production and operating tasks, or commercial and administrative tasks in the field. The programme also leads to doctoral study in Finland and internationally.
Modules
- Signal processing theory and algorithms
- Deep learning and neural networks
- Audio and speech processing
- Imaging and computer vision
- Statistical modeling and data analysis
- Imaging
- Machine hearing and vision
- Signal processing and data analysis
