Master in Data Science
University of Helsinki
Key Information
Campus location
Helsinki, Finland
Languages
English, Finnish, Swedish
Study format
On-Campus
Duration
2 years
Pace
Full time
Tuition fees
EUR 18,000 / per year *
Application deadline
Request info
Earliest start date
Aug 2024
* for non-EU/EEA countries
Introduction
How to prevent shipwrecks with the help of big data?
Data science combines computer science and statistics to solve exciting data-intensive problems in industry and many fields of science. As data is collected and analysed in all areas of society, the demand for professional data scientists is high and will grow even further.
In the interdisciplinary Master's Programme in Data Science, you are trained to work in data-intensive areas of industry and science, with the skills and knowledge needed to construct solutions to complex data analysis problems.
You can specialise either in the core areas of data science -- machine learning and 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.
Studying
The Data Science MSc degree consists of 120 credits divided into core courses, elective data science courses, and other courses.
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.
Students and Student Life
Student life and especially the student organisation culture is exceptionally rich and diverse in Finland. Also at the University of Helsinki, the student community is very active.
More than 250 student organisations operate within the Student Union of the University of Helsinki (HYY), ranging from faculty and subject organisations to political and societal organisations, and from choirs and orchestras to sports and game clubs. Their activities include anniversary celebrations, academic dinner parties, cultural events, get-togethers and excursions.
As a student and member of the Student Union (HYY), you are entitled to many benefits and services. For example, affordable student housing, basic healthcare services, sports facilities and student-priced meals. You also get numerous discounts, for example on public transport fees across the country.
Admissions
Curriculum
Core studies 35 cr
4 obligatory data science courses (20 cr)
Obligatory studies on professional data science skills: academic skills, seminar and project (15 cr)
Specialisation studies 25-55 cr
At least 5 elective data science courses from a given list (25-55 cr)
Other studies (0-30 cr)
A free choice of any courses/modules in any subject (0-30 cr)
Thesis work 30 cr
Master's thesis (30 cr)
Master's thesis
In the Master’s thesis, you will demonstrate your familiarity with the thesis topic, mastery of the necessary research methods, the ability to think scientifically and proficiency in academic writing. 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. The thesis workload, including the collection and processing of the research material as well as the writing process, corresponds approximately to one term of full-time study.
Ways to Study Data Science
There are many ways to study data science at the University of Helsinki. Some of the options include:
Obtain an MSc degree in Data Science in our programme
- You can apply in the yearly application round in January (unless you fall under the exceptions below).
- For students in the Faculty of Science bachelor programmes who have started in 2017 or later, please see the faculty instructions for selecting your MSc program.
- For all students in the Faculty of Science who have started before spring 2017, please see the faculty transfer tables.
Take individual data science courses and modules offered by our programme
- See the recommended modules for other degree programmes for more information. Individual lecture courses can also be taken even if you are not a student of our programme.
- While these courses and modules will not give you a degree in data science, they serve as an introduction to data science topics and will count towards your degree, should you later decide to apply to the Data Science MSc Programme.
Take domain-specific data science courses from other programmes
- Other faculties and programmes offer data science courses tailored for their fields. For instance, data science courses are offered within digital humanities, computational social sciences and life science informatics. Please see their web pages for information on the courses and their pre-requisities.
Take other generic method studies useful for data science
- Other programmes offer courses on methods that can be applied in data science as well. Examples of such programs include computer science, mathematics and statistics, and language technology. Please see their web pages for information on the courses and modules and on their prerequisites.
The Data Science MSc programme offers modules for students in other programmes. Individual lecture courses can also be taken by other students.
Gallery
Program Outcome
Why Data Science?
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; and
- Analyse scientific and industrial data to devise new applications and support decision-making.
Scholarships and Funding
Our scholarship program is for students who are applying to the University of Helsinki. These scholarships are intended for excellent students from outside the EU/EEA, who wish to complete a Master's program at the University of Helsinki. Grants can be applied while applying to the University of Helsinki’s Master’s programs.
Career Opportunities
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, 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.