M.S. Computing Sciences – Signal Processing and Machine Learning
Computing Sciences – Signal Processing and Machine Learning at Tampere University is an engineering programme, with a particular emphasis on speech and audio; imaging and vision; media, retrieval, and mining.
Quick Facts |
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Full-time Duration: | 2 years |
Starting in: | August |
Tuition Fee: | € 12,000/year |
Location: | Tampere, Finland |
Computing Sciences – Signal Processing and Machine Learning at Tampere University studies both classical and novel deep learning models as well as their software and hardware implementations. The programme enjoys strong ties with the related industrial ecosystems such as Tampere Imaging Ecosystem, Forum for Intelligent Machines, and Photonics Finland.
Signal processing is essentially about modeling and analyzing data representations of various phenomena of life, nature, society, economy, and culture. Modern signal processing leverages the strong predictive power of machine learning while enjoying the genetic connections with computer science and statistics.
Experts in Signal Processing and Machine Learning are much needed as the related applications are infinite: from creating data-driven solutions for medical
Career:
After completing the programme, you will be qualified to pursue a wide range of career opportunities in different fields of technology. The skills of data-driven problem solving are in high demand. This can be seen, for example, in surveys that demonstrate that signal processing, data and machine learning engineers are among the highest-paid of all related professionals. Tampere is a vibrant industrial hub for various types of companies with needs for signal processing and machine learning experts.
“The quality of life in here is so much better than in lots of countries. Tampere is a lovely town. I am slightly older than average students, and Tampere has got everything I need.“
Joseph // United Kingdom // Master’s degree programme in Internet and Game Studies
Study content
- Data Science
- Statistical Data Analytics
- Signal Processing and Machine Learning
- Human-Technology Interaction
- Software, Web & Cloud