Master's Programme in Data Science – Data Engineering

With a Master's degree in Data Science, specialising in Data Engineering, you will learn how to process data on distributed and high-performance computer systems to extract knowledge from large amounts of data. You will possess knowledge with a large area of application, from helping to solve the great societal problems of our time to working at companies of all sizes and areas to identify target groups and optimise their products and revenues.

Expand the information below to show details on entry requirements, programme-specific documents, selection criteria and tuition fees.

Autumn 2026 Autumn 2026, Uppsala, 100%, On-campus, English

Location

Uppsala

Pace of study

100%

Teaching form

On-campus

Instructional time

Daytime

Study period

31 August 2026–4 June 2028

Language of instruction

English

Entry requirements

Academic requirements

A Bachelor's degree, equivalent to a Swedish Kandidatexamen, from an internationally recognised university.

Also required is:

80 credits in computer science and mathematics;
15 credits in computer science including 10 credits in programming;
30 credits in mathematics including 5 credits in linear algebra, 5 credits in several variable calculus and 5 credits in statistics and probability.

Language requirements

Proficiency in English equivalent to the Swedish upper secondary course English 6. This requirement can be met either by achieving the required score on an internationally recognised test, or by previous upper secondary or university studies in some countries.

Selection

Students are selected based on an overall appraisal of previous university studies, a curriculum vitae (CV) and a statement of purpose.

Tuition fee-paying students and non-paying students are admitted on the same grounds but in different selection groups.

Fees

If you are not a citizen of a European Union (EU) or European Economic Area (EEA) country, or Switzerland, you are required to pay application and tuition fees.

First tuition fee instalment: SEK 75,000
Total tuition fee: SEK 300,000

About the programme

The Master's Programme in Data Science with a specialisation in Data Engineering will provide you with the knowledge, tools and skills to succeed in a wide range of different positions that involve the analysis of large amounts of data. This specialisation provides the general skills needed by a data scientist, as well as advanced skills in data mining, data engineering, accelerator-based programming, and security. The programme also covers the mathematical foundations of data science.

During the programme, you can expect to:

learn how to extract knowledge from large amounts of data,
get an understanding of both the mathematical foundations of data science and its computational aspects,
understand the importance of efficient and effective data processing, while still learning skills on how to model and understand data.

Companies such as Netflix and Amazon collect user data to generate predictions and recommendations about what their users will enjoy in the future. To analyse data produced by large-scale scientific experiments, advanced machine learning algorithms and data engineering platforms are needed. Many municipal authorities also strive to collect and integrate data from several types of sensors (air quality, sound, water distribution, and such). In all these examples, a single profession plays a pivotal role in turning information into insight: the data scientist.

As part of the programme, you will also delve into the ethical and legal aspects of data science, that are fundamental to address societal issues such as climate change, healthcare and democracy.

Uppsala University offers a rich research environment in data science, and the programme will prepare you for active participation in research projects, either as a PhD or in the industrial sector.

Student profile

You are someone with a theoretical foundation in mathematics and computer science, and curiosity about how large and complex sets of data can be utilised to solve a variety of real-life problems.

Degree

The programme leads to the degree of Master of Science (120 credits) with Data Science as the main field of study.

Content

The programme consists of three main parts.

Part 1

During the first semester you read core data science courses, for example about ethics and machine learning, together with the other specialisation in the programme. During this semester you can also choose courses to complete your basic knowledge in either computer science or mathematics, depending on your previous studies.

Part 2

From the second semester you can choose courses within the specialisation of data engineering, covering topics such as data mining, distributed computing, and security.

Part 3

From the third semester you start applying your knowledge and skills to solve complex problems: a project course at a research lab or in collaboration with students from other programmes, and a Master's thesis at a company or research lab.

Compared with the Master's programme in Statistics and Data Science, the Master's programme in Data Science focuses on state-of-the-art methods in computing and artificial intelligence. It also focuses on the design of data engineering systems supporting the analysis of very large data through high-performance and distributed computing. Ethical, legal, and application-related aspects of data science also have an important role in the programme, through dedicated courses.

Courses within the programme

See the programme outline for the courses within the specialisation.

Learning experience

Students are expected to participate and actively contribute to teaching sessions while also assuming responsibility for their own learning.

Instruction consists of lectures, practical assignments, seminars, and projects. A large part of the programme is spent studying on your own or in a study group outside the classroom, and as such, you must take a proactive role in structuring your studies. In a seminar, you present your ideas and discuss with your classmates a course book or other study material that you are required to read before the seminar; while the teacher usually only moderates the discussion. The aim is to develop critical thinking and collaborative skills. All the students are expected to be active participants in all forms of discussions.

Courses will include exam forms such as written examinations, oral examinations, lab sessions and project assignments with group examinations, case studies and written assignments.

The programme is intimately tied to contemporary research, and the courses closely follow current developments in data science.

The language of instruction is English.

Career

Data scientists can expect a strong labour market, as demand for the profession has long enjoyed steady growth. Data science is one of the most sought-after qualifications both in Sweden and internationally, and basic research in universities and academia has a large demand for data science to utilise the data generated by facilities such as SciLifeLab and Max IV. As such, you will enter the labour market with promising employment prospects.

Several independent analysts are predicting even greater demand in the field of data science, due to the ever-increasing level of automation and digitalisation. If you so desire, you may also choose to remain in academia and pursue PhD studies in data science. The faculty hosts several research groups, and doctoral positions are regularly offered.

Career support

During your time as a student, UU Careers offers support and guidance. You have the opportunity to take part in a variety of activities and events that will prepare you for your future career.

Other specialisations of the programme

Admitted or on the waiting list

Find information about the programme start and registration in the student gateway.

Student at Uppsala University

As a student, you will find information about your studies in the Student Gateway.

Master's Programme in Data Science – Data Engineering

Autumn 2026 Autumn 2026, Uppsala, 100%, On-campus, English