Detalji tečaja

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.

Jezik

Ključne riječi

Ciljana skupina

Vrsta tečaja

Obrazovna razina

ECTS bodovi

Broj polaznika

Način izvođenja

Miješano

Razina planiranja

Jednostavna

Status

U planiranju

Javni pristup tečaju

Zaključano

Razine korištenja AI-a

Ishodi učenja

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.

Razumijevanje

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

Razumijevanje

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

Evaluacija

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

Primjena

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