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 minor studies in the MSc programme, or it might already be part of your bachelor-level degree.

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.

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.

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)

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.

Minor studies give you a wider perspective of Data Science. Your minor subject 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)

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. 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.