Signal Processing and Machine Learning, Computing Sciences
The way we communicate and discover life
Extent of studies
Tuition fee for non-EU/EEA citizens
Link to scholarship programme
Information is conveyed by signals. People communicate across cities and continents, record and listen to music, preserve memories in videos, explore cosmic immensities and oceanic depths all enabled by signal processing. Doctors save lives by using signals, financiers predict economy trends, and directors create art performances likewise with the help of signal processing. The IEEE Signal Processing Society has said it most concisely: ‘Signal processing is the science behind our digital lives’
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 and biological problems; to enabling self-driving cars and autonomous robots.
Signal Processing and Machine Learning is an engineering programme, with a particular emphasis on speech and audio; imaging and vision; media, retrieval, and mining. We study 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 and Machine Learning (MSc Tech) specialisation is one of the seven specialisations in the Master’s Programme in Computing Sciences.
Detailed information on the content and structure of the studies is included in the curriculum.
Become a student
Learn more about the studies, admissions, and eligibility criteria on Studyinfo. In addition, applications are submitted via the Studyinfo.fi service.
For more information
Please read through the information provided. For further questions regarding the application process, contact our Admissions office at firstname.lastname@example.org or for questions regarding the content of the programme, please Ms. Anna-Mari Viitala, email@example.com.