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  • Study Type

    Full time available

  • Subject Areas

    Computer Science

    Mathematics

  • Start Date

    September

  • Course Duration

    2 years

  • Course Type

    MSc

  • Course Fees

    Tuition fee per year (non-EU/EEA students): 15000 €

  • Last Updated

    20 October 2017

Course content

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.

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).


Visit the Data Science - MSc page on the University of Helsinki website for more details!

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