Useful links:

• Slides and Assignments — Coming Soon.
• Official Syllabus
• Studium page - Coming Soon

This is a first course in machine learning. The course covers basic supervised and unsupervised methods (for example, regression, classification, decision trees, clustering), use of established tools for machine learning, application of the methods to real data, and practical aspects such as dimensionality reduction and cross validation. The course also introduces ethical aspects of bias in machine learning.