Machine learning (5 cr)

Objective

You understand the principles of artificial intelligence and machine learning.
You can determine what type of machine learning is appropriate for a given task.
You can do small artificial intelligence projects.

Content

How does artificial intelligence work?
How can machine learning be classified?
What are the different machine learning solutions suitable for?
How can simple artificial intelligence solutions be made?

Evaluation

Students can
use professional vocabulary and concepts in an expert way in different situations.
evaluate information sources critically.
work as team members in working life expert duties and identify and describe the problems of the professional field.
evaluate operations in customer, user and target group situations.
choose appropriate models, methods, software and techniques according to the purpose and justify these choices.
promote teams’ goal-oriented operation.
apply critically the ethical principles of the professional field in different situations.

Course material

Web materials

Study forms and methods

Individual learning tracks should always be discussed with the lecturers

RDI and work-related cooperation

The course may have assignments made for companies or assignments agreed individually with students.

Student workload

1 cr = 27 hours work

Evaluation scale

1-5

Assessment methods and criteria

There are multiple lecturers in the course and final evaluation is based on the individual evaluations of the lecturers and the evaluation of the final project(s)