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Signal Processing and Machine Learning, Computing Sciences

Tampere University
2 years
Master's degree
Scholarships available
On campus
Tampere
English
August 2022
Application deadline: 12 January 2022
Webinars
12/14/2021
Webinars
1/11/2022
Tampere University

Program description

Signal Processing and Machine Learning, Computing Sciences

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.

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Admission requirements

General eligibility

To be eligible to apply to a master’s programme at Tampere University, you must have:

  1. Bachelor’s degree - nationally recognized first cycle degree
    • an applicable bachelor’s degree at a university or a university of applied sciences in Finland
    • a bachelor's degree completed in a university outside Finland which provides eligibility for equivalent University master’s degree studies in the country in which it was awarded.
      • with a minimum scope of 180 ECTS credits, three to four years of full-time study
      • from a relevant field for the master’s degree programme that you’re applying to
      • from a recognised institution of higher education
  2. A good command of the English language for academic purposes.

Program-specific eligibility criteria

The previous degree should be from a field closely related to the Master's program you are applying to. In the Master’s program in Computing Sciences, Machine Learning (MSc tech) track, the previous degree has to be in one of the following (or highly related) fields:

  • computing, information technology, computer science, electrical engineering, software engineering or applicable field of engineering with proficiency in mathematics, physics and elementary programming skills.

For more information about admission requirement, please visit the university website.


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Program content

The signal processing and machine learning courses cover both theory and practice. They address a wide spectrum of areas such as speech and audio; imaging and vision; media, retrieval, and mining. Machine learning techniques in classification, regression, unsupervised learning and reinforcement learning (robotics) settings are taught. This is a module driven by strong research and we keep it up to date with the rapid advancements made in the field. We aim at integrating students in research groups and involving them in solving challenging research problems.

Tampere University offers students the opportunity for a broad, cross-disciplinary education. A rich variety of minor studies and supplementary courses are available as well as the opportunity to concentrate purely on major studies. In fact, each degree is a unique combination of studies that the individual student has found most interesting.

Scholarships & funding

Several scholarship options are available. Please visit the university website for more information.

Tuition fees

Tuition fee for non-EU/EEA citizens: 12000 € per academic year.

You will not be required to pay the fee if you are:

  • an EU/EEA citizen
  • equivalent to EU/EEA citizen (i.e. citizen of Switzerland)
  • already reside in Finland (a continuous A or a permanent P/P-EU residence permit), or have an EU Blue Card issued in Finland. The exempting residence permit must be valid when you are applying for studies and at least until 1 August i.e. when the study right commences. Please note that a residence permit in another EU/EEA country does not exempt you from the tuition fee.

Qualification

Degree earned

Master of Science (Technology)

Extent of studies

120 ECTS

Study objectives

We teach how to work with signals: their sensing, conversion, representation, enhancement, compression, rendering, synthesis, visualization, and quality assessment. We go deeply into modelling and analysis of signals, departing from classical signal processing, which is about signal sampling, reconstruction, estimation, and inference; exploring in depth modern signal processing, which is about signal sparsification and over-complete representations, to reach the lands of machine learning, where we navigate through CNN, GAN, GNN and many other neural networks. Eventually, we study the related hardware and software design, which is about sensors, computing platforms, GPU, end devices (e.g. displays), and user interfaces

Continuing studies

Following the successful completion of the program, graduates are eligible to apply for entrance to doctoral programs in Finland and abroad.

Career opportunities

After completing the program, 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 data and machine learning engineers are among the highest-paid of all professional programrs. Tampere is a vibrant industrial hub for various types of companies with needs for machine learning experts.

Graduated Master’s of Science typically find employment in research, design, development, production and operating tasks, or commercial and administrative tasks relating to the field, without excluding abilities to work as a researcher, teacher or manager.

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About this institute

Tampere University

Tampere University is one of the most multidisciplinary universities in Finland. Almost all internationally recognised fields of study are represented at our university. Tampere University is a merger of the former University of Tampere and Tampere University of Technology. University...


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Contact info

Tampere University

Kalevantie 4
33100 Tampere
Finland

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www.tuni.fi

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