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Machine learning (5cr)

Code: DA00EK58-3004

General information


Enrollment
10.11.2025 - 21.11.2025
Registration for introductions has not started yet.
Timing
12.01.2026 - 31.05.2026
The implementation has not yet started.
Number of ECTS credits allocated
5 cr
Local portion
0 cr
Virtual portion
5 cr
Mode of delivery
Distance learning
Unit
Department of Business
Campus
Ecampus
Teaching languages
Finnish
Seats
20 - 60
Degree programmes
Degree Programme in Data Analytics
Teachers
Atte Reijonen
Jarkko Ansamäki
Teacher in charge
Jarkko Ansamäki
Groups
DAKV24SV
Data analytics, online studies
Course
DA00EK58

Realization has 4 reservations. Total duration of reservations is 6 h 0 min.

Time Topic Location
Fri 30.01.2026 time 12:50 - 14:20
(1 h 30 min)
Koneoppiminen DA00EK58-3004
Etäopetus lukujärjestyksen mukaan
Fri 06.03.2026 time 14:30 - 16:00
(1 h 30 min)
Koneoppiminen DA00EK58-3004
Etäopetus lukujärjestyksen mukaan
Fri 10.04.2026 time 10:40 - 12:10
(1 h 30 min)
Koneoppiminen DA00EK58-3004
Etäopetus lukujärjestyksen mukaan
Fri 10.04.2026 time 12:50 - 14:20
(1 h 30 min)
Koneoppiminen DA00EK58-3004
Etäopetus lukujärjestyksen mukaan
Changes to reservations may be possible.

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.

Timing of exams and assignments

-

International cooperation

-

Student workload

1 cr = 27 hours work

Course part description

-

Further information

Opiskelijan tulee hallita R-ohjelmoinnin perusteet. Ne voi hankkia suorittamalla samaan aikaan pidettävän Tilastolliset menetelmät -kurssin tai kertausmateriaalien avulla. Suosittelemme kurssien samanaikaista suorittamista.

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)

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