Introduction to Machine Learning
7.5 credits
The course covers machine learning concepts and methods. The following topics are covered in the course:
• basic statistical concepts
• supervised and unsupervised learning
• linear and polynomial regression,
• logistic regression
• decision trees
• Support vector machines
• unsupervised learning using the k-means clustering algorithm
• algorithm evaluation using cross-validation and mean square error
• evaluation metrics such as precision, recall, and F-score
• algorithm implementation using MATLAB
Distance – study where you are
Perhaps you would like to study in the Swedish mountains, in a big city, or at home close to family? Many of our programmes and courses are offered in distance format.
Studying at a distance can be done in different ways, either entirely without physical gatherings or with only a few gatherings on campus or at one of our learning centres. The common denominator is that a large part of your studies takes place online. You communicate with the teacher and other students with the help of a learning platform with discussion forums, group work, recorded lectures and online meetings.
The benefit of distance studies is the flexibility, something that is valuable if you want to be free to decide when and where you want to study. Some compulsory elements on you course or programme may take place during office hours, even though they are online.
Build your own degree
Did you know that you can combine single-subject courses to build your own degree? In this way, you can design your own degree based on your interests and the career you are aiming for. This does not apply to all courses so make sure to check with a study counsellor at the faculty. Learn more about how you can build your own degree and become unique on the labour market.