Are you interested in immersing yourself in large amounts of data? Maybe you want to develop your knowledge to help solve some of today's societal problems. With a Master's degree in Data Science, specialising in machine learning and statistics, you'll learn how to make advanced statistical analyses and extract knowledge from large amounts of data. With this knowledge, you'll be able to work at any company to identify its target groups and optimise its products and revenues.
Why this programme?
The Master's Programme in Data Science with a specialisation in Machine Learning and Statistics 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 machine learning, reinforcement learning, computer-intensive statistics, and selected mathematical topics in Data Science.
During the programme you can expect to:
Learn how to make advanced statistical analyses
Gain a robust understanding of both the mathematical foundations of data science and its computational aspects
Work alongside internationally renowned research teams in data science
Delve into the ethical and legal aspects of data science
Companies such as Netflix, Amazon and Spotify collect user data to generate relevant predictions and recommendations about what their users will enjoy in the future. In order to analyse data produced by large-scale scientific experiments, advanced machine learning algorithms and data engineering platforms are needed. Many authorities also strive to collect and integrate data from several different types of sensors (air quality, sound, water distribution, and such). For this, a single profession plays a pivotal role in turning information into insight: the data scientist.
The labour market forecasts for data analysts are good, and the profession has long had strong growth. Data analyst is one of the most sought-after competencies both in Sweden and internationally. Thus, you will be faced with a strong job market after graduation.
Uppsala University also offers a rich and vital research environment in data science, with a large number of researchers from several different institutions, and the programme will prepare you for active participation in research projects, either as a PhD or in the industrial sector.
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.
The programme leads to a Master of Science (120 credits) with Data Science as the main field of study.
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, and 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.
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.
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 MaxV. 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 till 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.
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. Learn more about UU Careers.
Below you will find details about eligibility requirements, selection criteria and tuition fees. For information on how to apply and what general documents you need to submit, check the application guide. Besides the general supporting documents, you also need to submit two programme-specific documents: 1. a CV; 2. an Application Summary Sheet (including your statement of purpose).
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 5 credits in introductory programming;
25 credits in mathematics including linear algebra and several variable calculus; and
5 credits in statistics and probability.
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. Detailed instructions on how to provide evidence of your English proficiency are available at universityadmissions.se.
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.
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. Fees cover application and tuition only and do not cover accommodation, academic literature or the general cost of living. Read more about fees.