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Master's Degree Programme in Information and Communication Technology: Data Analytics

The Master's Degree Programme in Information and Communication Technology provides versatile and high-quality ICT education in selected fields of ICT, with an established reputation in innovative, interdisciplinary, and international education.

Extent of the Study Programme

• The extent of the study programme is 120 ECTS.
• The planned duration is 2 academic years.
• The tuition fee is free for citizens of EU/EEA countries or Switzerland, and €12,000 per academic year for citizens of non-EU/EEA countries.
• The qualification awarded is Master of Science (Technology).
• Studies begin in late August 2026.
• The location of the programme is Turku, Finland.
• The language of instruction is English.
• The mode of teaching is contact teaching.

Faculty and Annual Quota

• The programme is offered by the Faculty of Technology.
• The annual quota for the MDP in Information and Communication Technology is 55.

Application Period and Entry Requirements

• The application period is January 2026.
• Entry requirements include a nationally recognized first-cycle degree, corresponding to at least 180 ECTS or three years of full-time study, in a relevant field for the Master's degree programme.
• Applicants must have excellent English language skills, proven by an internationally recognized English language test.
• The applicant's previous degree must be in a relevant field of study, such as Computer Science, Computer Technology, Information Technology, or other relevant fields, provided that sufficient knowledge of programming is achieved.

Programme Structure

• A. Advanced-level studies in the major subject: 50 ECTS
• B. Thematic module or minor subject: 20-25 ECTS
• C. Other studies: 15-20 ECTS
• D. Master of Science in Technology Thesis: 30 ECTS

Data Analytics Track

• The Data Analytics track trains specialists for the effective utilization and communication of data in research, decision-making, and society.
• The focus of teaching is on understanding and applying the operational principles of the key data analysis methods in practice.
• Teaching in the field is linked to the current research themes of the Department of Computing, from health technology to computational humanities and from language technology to intelligent systems.

Research

• The research of the data analytics team is currently organized in three laboratories: Algorithmics and Computational Intelligence (ACI), Natural Language Processing (NLP), and Data Science.
• The research combines theory and methods of algorithmic data analysis, with a particular focus on probabilistic machine learning, complex systems, high-throughput data analysis, and statistical programming.

Master's Thesis and Topics

• In the Master's thesis, the student must prove their ability to do scientific work and mastery of research methods, knowledge of the research field, and skills in scientific writing.
• The thesis is often commissioned by a company, which means that an efficient and capable student could be directly employed by the commissioning company, giving a head start to a career in industry.

Career Prospects

• After completing a degree in data analytics, graduates are aware of the main methods of data analysis, their theoretical basis, their possibilities, and their limitations.
• Graduates can apply scientific methods in the field and either find existing or develop their own methods for data analysis.
• The need for the effective utilization and communication of data in research, decision-making, and society is growing rapidly, offering diverse career opportunities for those skilled in the field.
• Data analytics is widely applicable in various sectors of society, and the exploitation of explosively increased data requires specialists who are in high demand in the labor market.

Competence Description

• Graduates achieve multidisciplinary competencies that support diverse professional development and lifelong learning in changing work environments.
• They master the central cooperation and oral and written communication skills required in working life.
• Graduates know how to work and get around in a multidisciplinary and multicultural work environment.
• They understand the importance of science and technology to the individual, society, the environment, and are ready for postgraduate scientific studies in data analytics and related fields.