Lifewide learning courses and programmes

Machine learning: Supervised methods

Course will address topics such as generalisation error analysis and estimation, optimisation and computational complexity, linear models, support vector machines and kernel methods, feature selection and sparsity, multi-class classification, ranking and multi-output learning.


Teaching time:



Information and communications technology

Form of learning:

Exam Online


Aalto University, FITech




5 By Aalto University (ECTS)


€ 0.00

Application period:

1.6.2023 – 28.8.2023

Target group and prerequisites

Courses Machine Learning, Statistical inference or equivalent knowledge. Basics of probability theory and linear algebra. Programming skills. Mastering the prerequisite skills is very important in order to complete this course.

Course description

Course contents

  • Generalisation error analysis and estimation
  • Model selection
  • Optimisation and computational complexity
  • Linear models
  • Support vector machines and kernel methods
  • Boosting
  • Feature selection and sparsity
  • Multilayer perceptrons
  • Multi-class classification
  • Ranking
  • Multi-output learning

Learning outcomes

After the course, the student

  • knows how to recognise and formalise supervised machine learning problems,
  • knows how to implement basic optimisation algorithms for supervised learning problems,
  • knows how to evaluate the performance supervised machine learning models,
  • has understanding of the statistical and computational limits of supervised machine learning, as well as the principles behind commonly used machine learning models.

Teaching schedule

Lectures (Otaniemi) will be held on Tuesdays at 10:15-12:00. Exercise sessions (in Otaniemi) will be held on Fridays at 10:15-12:00. Attendance in lectures and exercise sessions is voluntary, recordings from lectures available. The exam is in Otaniemi.

Completion methods


  • 24 lecture hours
  • 12 hours exercise session
  • 3 hours exam
  • 96 hours independent study
  • Updated: