Back to all courses

Machine learning for mobile and pervasive systems

Individual course

Max amount of FITech students: 25

During this course, students will learn good practices for machine learning with noisy and inaccurate data.

Course contents

Feature extraction/feature subset selection, handling high dimensional data, ANN + deep learning, probabilistic graphical models, topic models as well as unsupervised learning and clustering, anomaly detection and recommender systems.

Course material

Lecture handouts/slides.

Teaching schedule

Lectures on Wednesdays & Fridays at 14–16.

Completion methods

Examination, assignments and group works.

More information in the Aalto University study guide.

You can get a digital badge after completing this course.

Responsible teacher

Aalto University
Stephan Sigg

Contact person for applications

FITech Network University
Fanny Qvickström, Student services specialist
Application period has ended
Application period has ended
5G technology,
AI and machine learning
Course code:
Study credits:
0 €
Course level:
Teaching period:
Application deadline:
Application period has ended
Host university:
Aalto University
Who can apply:
Adult learner
Teaching method:
Place of contact learning:
Teaching language:
General prerequisites:
Recommended: skilled in programming.
Interested in this course? Subscribe and get updates about the course directly to your email. You can cancel subscription any time you want.