For more information about Master's Programme in Data Science at University of Helsinki, please visit the webpage using the button above.

The award
MSc

How long you will study
2 years

Domestic course fees
find out

How you will study
full-time

Course starts
September

International course fees
EUR 15000 per year

All study options

About Master's Programme in Data Science at University of Helsinki

Goal of the programme

Data science combines computer science and statistics to solve exciting data-intensive problems in industry and in many fields of science. Data scientists help organisations make sense of their data. As data is collected and analysed in all areas of society, demand for professional data scientists is high and will grow higher. The emerging Internet of Things, for instance, will produce a whole new range of problems and opportunities in data analysis.

In the Data Science master's programme, you will gain a solid understanding of the methods used in data science. You will learn not only to apply data science: you will acquire insight into how and why methods work so you will be able to construct solutions to new challenges in data science. In the Data Science master's programme, you will also be able to work on problems specific to a scientific discipline and to combine domain knowledge with the latest data analysis methods and tools. The teachers of the programme are themselves active data science researchers, and the programme is heavily based on first-hand research experience.

Upon graduating from the Data Science MSc programme, you will have solid knowledge of the central concepts, theories, and research methods of data science as well as applied skills. In particular, you will be able to

  • Understand the general computational and probabilistic principles underlying modern machine learning and data mining algorithms
  • Apply various computational and statistical methods to analyse scientific and business data
  • Assess the suitability of each method for the purpose of data collection and use
  • Implement state-of-the-art machine learning solutions efficiently using high-performance computing platforms
  • Undertake creative work, making systematic use of investigation or experimentation, to discover new knowledge
  • Report results in a clear and understandable manner
  • Analyse scientific and industrial data to devise new applications and support decision making.

The MSc programme is offered jointly by the Department of Computer Science, the Department of Mathematics and Statistics, and the Department of Physics, with support from the Helsinki Institute for Information Technology (HIIT) and the Helsinki Institute of Physics (HIP), all located on the Kumpula Science campus. In your applied data science studies you can also include multidisciplinary studies from other master's programmes, such as digital humanities, and natural and medical sciences.

Further information about the studies on the Master's programme website.

Tuition fees

Citizens of non-EU/EEA countries, who do not have a permanent residence status in the area and pursue their studies in English, are liable to pay tuition fees.You can check from FAQ at the Studyinfo website whether or not you are required to pay tuition fees. Find out more about the Be 1* of the Best Scholarship Programme.

Information on the languages of instruction

All teaching is in English. You can also take exams and complete work, such as your Master's thesis, in Finnish or Swedish.

Programme contents

The Data Science MSc programme combines elements from computer science and mathematical sciences to provide you with skills in topics such as machine learning, distributed systems and statistical methods. You might also find that knowledge in a particular scientific field is useful for your future career. You can obtain this through elective studies in the MSc programme, or it might already be part of your bachelor-level degree.

Studies in the Data Science MSc programme include both theoretical and practical components, including a variety of study methods (lectures, exercises, projects, seminars; done both individually and in groups). Especially in applied data science, we also use problem-based learning methods, so that you can address real-world issues. You will also practise academic skills such as scientific writing and oral presentation throughout your studies. You are encouraged to include an internship in your degree in order to obtain practical experience in the field.

Elective studies give you a wider perspective of Data Science. Your elective studies can be an application area of Data Science (such as physics or the humanities), a discipline that supports application of Data Science (such as language technology), or a methodological subject needed for the development of new Data Science methods and models (such as computer science, statistics, or mathematics).

Selection of the study track

You can specialise either in the core areas of data science -- algorithms, infrastructure and statistics -- or in its applications. This means that you can focus on the development of new models and methods in data science, supported by the data science research carried out at the University of Helsinki; or you can become a data science specialist in an application field by incorporating studies in another subject. In addition to mainstream data science topics, the programme offers two largely unique opportunities for specialisation: the data science computing environment and infrastructure, and data science in natural sciences, especially physics.

Programme structure

You should be able to complete the MSc Programme in Data Science of 120 credits (ECTS) in two years of full-time study. The programme consists of

  • Common core studies of basic data science courses
  • Several modules on specific topics within data science algorithms, data science infrastructures and statistical data science, and on data science tools
  • Seminars and colloquia
  • Courses on academic skills and tools
  • Possibly an internship in a research group or company
  • Studies in an application domain
  • Master's thesis (30 credits)

Thesis

The programme includes a mandatory Master's thesis. Your Master's thesis will focus on a data science problem and on applying the knowledge you have learned during your MSc courses to solve that problem. The problem you address can be theoretical or practical in nature, but your thesis work must always have a research component and a scientific basis.

In your thesis you will demonstrate your ability to think scientifically, your command of research methods, your familiarity with the subject of study, and your aptitude for written scientific communication. Your thesis should contain a definition of the research questions, a review of the relevant literature, and theoretical, constructive or empirical parts developing answers to your research questions. 

You will have a supervisor appointed to oversee your thesis. You and your supervisor will have regular meetings to ensure that your work is progressing smoothly and on schedule. The thesis is worth 30 credits, roughly corresponding to one semester of full-time studies.

Although your thesis is independent work, you can often write it as part of a research group. You might also be able to write your thesis for a company as long as you fulfil the academic criteria described above. You can discuss these issues with your supervisor.

Career prospects

Industry and science are flooded with data and are struggling to make sense of it. There is urgent demand for individuals trained to analyse data, including massive and heterogeneous data. For this reason, the opportunities are expected to grow dramatically. The interdisciplinary Data Science MSc programme will train you to work in data-intensive areas of industry and science, with the skills and knowledge needed to construct solutions to complex data analysis problems.

If you are focusing on the core areas of data science, you will typically find employment as a researcher or consultant, sometimes after taking a PhD in Computer Science or Statistics to deepen your knowledge of the field and research methods. If your focus is on the use of data science for specific applications, you will typically find work in industry or in other fields of science such as physics, digital humanities, biology or medicine. 

Internationalization

The Data Science MSc is an international programme, with students from around the world and an international research environment. All of the departments taking part in the programme are internationally recognised for their research and a significant fraction of the teaching and research staff come from abroad.

The departments participate in international student exchange programmes and offer you the chance to include international experience as part of your degree. Data Science itself is an international field, so once you graduate you can apply for jobs in any country.

In the programme, all courses are in English. Although the Helsinki area is quite cosmopolitan and English is widely spoken, you can also take courses to learn Finnish at the University of Helsinki Language Centre. The Language Centre also offers an extensive programme of foreign language courses for those interested in learning other languages.

Networking

Education in the programme is multidisciplinary, combining the expertise of the Department of Computer Science, the Department of Mathematics and Statistics, the Department of Physics, the Helsinki Institute for Information Technology (HIIT) and the Helsinki Institute of Physics (HIP). The University of Helsinki offers a huge variety of possibilities for elective studies with which you can complement your data science expertise. For example, you can take advantage of courses offered by the MSc Programme in Life Science Informatics. Collaboration with Aalto University, through the joint institutes HIIT and HIP, gives you further opportunities.

Teaching in the programme is based on research carried out in the above-mentioned departments and institutes, often in collaboration with other fields of science, as well as with industry. Particle physics data analysis, for instance, is carried out in collaboration with CERN. An example of industrial cooperation is the Nokia Center for Advanced Research, a joint research centre between the University of Helsinki, Aalto University, and Nokia.

Research focus

The MSc programme in Data Science is offered jointly by three departments and two research institutes. Their research covers a wide spectrum of the many aspects of data science. At a very general level, the focal areas are

  • Machine learning and data mining
  • Distributed computation and computational infrastructures
  • Statistical modelling and analysis

Studies in the programme are tightly connected to research carried out in the participating departments and institutes.

Postgraduate studies

After completing the MSc programme in Data Science, you can apply for doctoral studies at the University of Helsinki or elsewhere. Due to the high level of international recognition of the University of Helsinki and the data science research groups, you will have good chances to be accepted for doctoral studies at top universities. The additional skills gained in doctoral studies will not only be useful for an academic research career but also for work as a data scientist in industry. At the University of Helsinki, suitable doctoral programmes include:

For more information, please see www.helsinki.fi/en/research/doctoral-education.

Competence

A Master's degree gives eligibility to apply to positions that require a second cycle academic degree i.e. a Master's level degree.

Study options for this course

Notes about fees for this course

Citizens of non-EU/EEA countries, who do not have a permanent residence status in the area and pursue their studies in English, are liable to pay tuition fees. You can check from FAQ at the Studyinfo website whether or not you are required to pay tuition fees.

Find out more about the Be 1* of the Best Scholarship Programme.

Entry requirements

Contact University of Helsinki to find course entry requirements.

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