Statistics: Master Course - Statistical Methods for Data Science (course package)

This course package gives you a solid foundation in modern statistics and data science. You will explore both classical and advanced analytical methods used to understand, model and predict patterns in large datasets. Throughout the courses, you will develop your skills in programming, machine learning, high-dimensional data analysis, reinforcement and deep learning, and text analytics.

The course package concludes with an independent master’s thesis, where you will investigate a practical or methodological problem within contemporary data science. This course package is well-suited for students who want to combine statistics, mathematics and programming to solve real-world challenges.

Statistics and data science form the foundation of many technologies we rely on every day – from search engines and social media to medical diagnostics and climate research. By analysing and interpreting data, you can contribute to better decision-making, innovative solutions and new discoveries across society.

Teaching consists of lectures, theoretical components and practical exercises using real-world datasets in Python and R.

You will:

• programme and implement a wide range of statistical and machine-learning methods
• work independently as well as in groups
• solve tasks that reflect real analytical challenges
• complete an individual thesis project in your chosen area

Theory and practice are closely integrated, ensuring that you can apply your knowledge directly in code and statistical analysis. 

Your knowledge will be assessed through course work, projects presented orally and in writing, quizzes and written examinations. 

After completing the courses in the course package, you will be well prepared for roles such as statistician, data scientist, analyst or other professions requiring advanced analytical skills.

If you pass all courses and meet the overall degree requirements, you may apply for a Master’s Degree in Statistics. This qualification also provides a strong foundation for further study at master’s or doctoral level.

Entry requirements

A Bachelor's degree in statistics, or a Bachelor's degree in mathematics or computer science including at least 60 credits in statistics, or the equivalent.

Selection criteria

Selection is based on the average grades of the qualifying courses in statistics with the highest grades. In total, grades from courses equivalent to 90 ECTS should be included.

Tuition fees for non-EU/EEA citizens

Citizens of countries outside:

• The European Union (EU)
• The European Economic Area (EEA) and
• Switzerland

are required to pay tuition fees. You pay an instalment of the tuition fee in advance of each
semester.

Tuition fees, payments and exemptions

Full programme/course tuition fee: SEK 150,000
First payment: SEK 75,000

Convert currency – xe.com

Note that you may also need to pay an application fee, or provide proof of exemption.

Application fee

No tuition fees for citizens of the EU, EEA and Switzerland

There are no tuition fees for citizens of the European Union (EU), the European Economic Area (EEA) and Switzerland.