Kurssin tiedot

A course in modern machine learning methods that covers theoretical and practical aspects. NOTE REGARDING THE WORKLOAD: The requirement is for each participant to complete 12 modules, a team project and a final exam. This works out to a workload of 180h. Since the number of modules available in the course is greater than 12, the total number of hours is greater than 180 – but these modules are not all to be taken by the same participants.

Kieli

Avainsanat

Kohderyhmä

Kurssityyppi

Koulutustaso

ECTS-opintopisteet

Oppijoiden määrä

Toimitustapa

Yhdistelmä

Suunnittelutaso

Yksinkertainen

Status

Suunnittelussa

Kurssin julkinen pääsy

Locked

AI usage levels

Oppimistavoitteet

The participant is able to explain basic concepts from the field of machine learning such as: machine learning, implicit and explicit knowledge representation, local and global generalization, underfitting, overfitting, bias, variance, regularization and more.

Ymmärtäminen

The participant understands and is able to explain the principle of fundamental machine learning methods.

Ymmärtäminen

The participant is able to assess where and how machine learning methods can be applied.

arviointi

The participant is able to apply machine learning methods and approaches.

Soveltaminen

The participant is able to identify machine learning problems and search for corresponding state of the art methods.