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Unsupervised Learning

Unsupervised learning is a type of machine learning, where instead of inferring a function from training data that can be used to map new examples, the task is to look for patterns in a data set without pre-existing labels.

Information for admitted students Spring 2021

Congratulations! You have been admitted at Stockholm University and we hope that you will enjoy your studies with us.

In order to ensure that your studies begin as smoothly as possible we have compiled a short checklist for the beginning of the semester.

Follow the instructions on wether you have to reply to your offer or not.


Checklist for admitted students

  1. Activate your university account

    The first step in being able to register and gain access to all the university's IT services.

  2. Register at your department

    Registration can be done in different ways. Read the instructions from your department below.

  3. Read all the information on this page

    Here you will find what you need to know before your course or programme starts.


Your seat may be withdrawn if you do not register according to the instructions provided by your department.

Information from your department

On this page you will shortly find information on registration, learning platform, etc.

Welcome activities

Stockholm University organises a series of welcome activities that stretch over a few weeks at the beginning of each semester. The programme is voluntary (attendance is optional) and includes Arrival Service at the airport and an Orientation Day, see more details about these events below.
Your department may also organise activities for welcoming international students. More information will be provided by your specific department. 

Find your way on campus

Stockholm University's main campus is in the Frescati area, north of the city centre. While most of our departments and offices are located here, there are also campus areas in other parts of the city.

Find your way on campus

Read more

New student

During your studies

Student unions

For new international students

Pre-departure information

New in Sweden

The course aims to introduce both basic and modern concepts in statistical learning without training data (unsupervised learning) with applications in statistical data analysis. Key concepts reviewed include similarity metrics, linear and nonlinear dimension reduction methods, centroid, distribution and density based methods for cluster analysis, visualization of high dimensional data, hierarchical methods and various validation methods.

You may also be interested in the course MT7038 Statistical learning, which focuses on supervised learning.