Master of Science (Technology) in Signal Processing and Machine Learning, Computing Sciences and Electrical Engineering
Tampere, Finland
DURATION
2 Years
LANGUAGES
English
PACE
Full time
APPLICATION DEADLINE
Request application deadline *
EARLIEST START DATE
Aug 2025
TUITION FEES
EUR 12,000 / per year **
STUDY FORMAT
On-Campus
* Application for studies starting in autumn 2025 begins 11 December 2024 and ends 3 January 2025
** per academic year for non-EU/EEA students
Key Summary
Introduction
The way we communicate and discover life
Information is conveyed by signals. People communicate across cities and continents, record and listen to music, preserve memories in videos, and explore cosmic immensities and oceanic depths all enabled by signal processing. Doctors save lives by using signals, financiers predict economic 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 program, 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 program enjoys strong ties with related industrial ecosystems such as Tampere Imaging Ecosystem, Forum for Intelligent Machines, and Photonics Finland.
Signal Processing and Machine Learning (MSc Tech) is one of the engineering specializations in the Master’s Programme in Computing Sciences and Electrical Engineering.
Admissions
Curriculum
Study contents
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 into 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.
Structure of studies
Master’s Programme comprises 120 ECTS credits. Each ECTS credit is about 27 hours of student work. Depending on the specialisation, courses are worth 80-90 ECTS, and the remaining 30-40 ECTS are awarded for successfully completing a master’s thesis. The duration of the programme is two years. Students usually spend three semesters completing courses and one semester preparing the Master’s thesis. The studies start in late August, and the academic year ends in late May.
Master’s Programme in Computing Sciences consists of seven specialisations, leading either to Master of Science, or Master of Science in Technology degree:
- Data Science (MSc)
- Signal Processing and Machine Learning (MSc Tech)
- Statistical Data Analytics (MSc)
and
- Human-Technology Interaction (MSc)
- Human-Technology Interaction (MSc Tech)
- Software, Web & Cloud (MSc)
- Software, Web & Cloud (MSc Tech).
Scholarships and Funding
Tampere University Tuition Fee Scholarships
Tampere University tuition fee scholarship is an exclusive opportunity awarded to a limited number of the best-performing applicants in each programme.
Tampere University tuition fee scholarships awarded at admission cover 50% of the tuition fees for the programme duration.
Early bird offer
While Tampere University scholarships are available to a limited number of applicants, the early bird offer is available at admission to all fee-paying students. The early bird offer gives a 1500 € reduction on the programme tuition fee during the first year of studies.
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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 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 a need for signal processing and machine learning experts.
Graduated Master of Science in Technology 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.
Following the successful completion of the program, graduates are also eligible to apply for entrance to doctoral programs in Finland and abroad.
Co-operation with other parties
Tampere university is a well-known institute among the companies in Tampere area, Finland and abroad. The university has a good reputation and has had a lot of co-operation with the companies during the years. This certainly helps the students to find valuable thesis-work opportunities in the companies, and most often, those students are employed by these companies once graduated.
In addition to studies in one’s own programme, students may take full advantage of the teaching offered by the Tampere higher education community ranging from technical to vocational studies in various fields.
Program Tuition Fee
Program Admission Requirements
Demonstrate your commitment and readiness to succeed in business school by taking the GMAT exam – the most widely used exam for admissions that measures your critical thinking and reasoning skills.
Download the GMAT mini quiz to get a flavour of the questions you’ll find in the exam.