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

General Requirement

You are an eligible applicant for Master’s degree studies if

• you have a nationally recognized first cycle degree – normally a Bachelor’s degree – from an accredited institution of higher education,
• your degree corresponds to at least 180 ECTS (European credits) or three years of full-time study,
• your degree is in a relevant field for the Master’s degree programme that you’re applying to. Please check the section on track-specific admission requirements for detailed degree requirements.

Language Requirements

Applicants must have excellent English language skills and a certificate that proves those skills. You can indicate your language skills by taking one of the internationally recognized English language tests.

Applicants must reach the minimum required test results to be eligible for the University of Turku. No exceptions will be made. Read more about the language requirements here.

Study right

It is not possible to have more than one Bachelor’s or Master’s study right at the same Faculty. Therefore, when accepting an offered study place, the student will lose any previous BSc. or MSc. study right at the Faculty of Technology at the University of Turku.

Before you start preparing your application, always read the full admission requirements on the application portal Studyinfo.fi

The applicant’s previous degree based on which s/he is seeking admission to the Master’s Degree Programme in Information and Communication Technology must be in a relevant field of study. Relevant fields of previous studies for the Data Analytics specialisation track are:

• Computer Science
• Computer Technology
• Information Technology
• Other relevant fields of study (e.g. statistics, mathematics, physics) provided that sufficient knowledge of programming is achieved.

You may not apply to more than one specialization track within the same Master’s Degree Programme at the University of Turku. Therefore, you should carefully consider the suitability of your educational background for the applied track.

The decision of admission will be based on:

• the relevance of the applicant’s awarded degree(s)
• the amount, relevance, and grades of the courses in the degree(s)
• the language test result (see Language requirements)
• the motivation letter and your answers to the programme-specific questions (instructed later)
• Curriculum Vitae including details on your academic and professional career
• the possible relevant work experience
• the possible interview.

The academic evaluation is made only for complete applications received during the application period. Any preliminary assessment of suitability or chances for admission will not be given.

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

See the curriculum. 

The University of Turku fosters students' professional growth and global perspective by promoting internships and student exchanges. Every degree student can take advantage of these opportunities – all internships come with a guaranteed subsidy, and every exchange programme includes a grant.

Does this page answer your questions about the programme's content and academic matters? If not, contact infoscitech@utu.fi.

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 of the ACI group is based on the long tradition of combining basic research on algorithm development and analysis with active cooperation with companies and academic partners on solving real-life problems by the use of combinatorial optimization and latest techniques on Artificial Intelligence and especially machine learning. 

The NLP group studies various aspects of natural language processing, human language technology and digital linguistics, with a distinct focus on machine learning methods.

The Data Science group's 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. The main application areas are in computational humanities and molecular life sciences.

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. In writing the Master’s thesis, the student needs to apply their technology skills, abilities and expertise to identify an engineering problem, study its relevance to the field, propose and design a solution, and test and analyse the solution and evaluate its usefulness.

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. On the other hand, an academically-oriented student might choose a thesis topic related to research conducted by one of our research groups, and apply for the position of doctoral candidate upon completion of an academically distinguished Master’s thesis.

After completing a degree in data analytics, you

• are aware of the main methods of data analysis, their theoretical basis, their possibilities and their limitations;
• can apply scientific methods in the field and either find existing, or, when necessary, develop your own methods for data analysis;
• can search and critically evaluate scientific literature;
• acquire the skills based on the latest research for wide-ranging and responsible expert and management positions in the field of data analysis and more broadly in ICT;
• achieve multidisciplinary competencies that support diverse professional development and lifelong learning in changing work environments;
• master the central cooperation and oral and written communication skills required in working life;
• know how to work and get around in a multidisciplinary and multicultural work environment;
• 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.

Data and data analytics are the cornerstones of digitalization and artificial intelligence.

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. The importance of open and transparent data has also grown, hence creating opportunities for a rapidly growing range of services and businesses. Knowledge management has become one of the most important factors in the competitiveness of companies, and data analytics plays a key role in this.

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.

Master's Degree (Technology) provides eligibility for scientific postgraduate degree studies. Postgraduate degrees are doctoral and licentiate degrees. Degrees can be completed within the University of Turku Graduate School.