Master's Programme in Data Science – Machine Learning and Statistics

The programme consists of four main parts. At first, you and your fellow students may have different backgrounds, and therefore you can choose courses to complete your basic knowledge in computer science and mathematics. You can also choose to take core data science courses, for example on data ethics and law, statistical machine learning, and the theoretical foundations of data science and data engineering.

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 artificial intelligence, machine learning, and mathematical statistics. 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.

From the end of the first year, you choose courses within the specialisation of machine learning and statistics covering topics such as reinforcement learning and advanced probabilistic machine learning. The programme also includes practical activities, such as a project course done at a research lab or in collaboration with students from other programmes.

You will also conduct a Master's thesis that is required to obtain the degree and you can do it at a company or research lab.

Courses within the programme

See the programme outline for courses within the specialisation.

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 own 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.

Data scientists can expect a strong labour market, as demand for the profession has long enjoyed strong 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 be faced with a strong labour market upon completion of your degree.

Several independent analysts are predicting even greater demand in the field of data science, due to the ever-increasing level of automation and digitalisation. In 2017, LinkedIn published a report on new career opportunities in the US which found that the two professions enjoying the largest increase in demand were machine learning engineer and data scientist. According to IBM, the number of data science positions will increase by 39 per cent in 2020. One of the largest Swedish work unions SACO has also published a prediction for the data engineering labour market in Sweden until 2023 and it shows the demand will remain high.

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 sometimes 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.