Machine learningLaajuus (5 cr)
Code: DA00EK58
Credits
5 op
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?
Enrollment
04.11.2024 - 17.11.2024
Timing
13.01.2025 - 31.05.2025
Number of ECTS credits allocated
5 op
Virtual portion
5 op
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
-
DAKV23SVData analytics, online studies
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?
Opiskelumateriaali
Web materials
Yksilölliset oppimisväylät
Individual learning tracks should always be discussed with the lecturers
TKI ja työelämäyhteistyö
The course may have assignments made for companies or assignments agreed individually with students.
Opiskelijan työmäärä
1 cr = 27 hours work
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)
Enrollment
06.11.2023 - 17.11.2023
Timing
08.01.2024 - 31.05.2024
Number of ECTS credits allocated
5 op
Virtual portion
3 op
Mode of delivery
40 % Contact teaching, 60 % Distance learning
Unit
Department of Business
Campus
Kouvola Campus
Teaching languages
- Finnish
Seats
20 - 60
Degree programmes
- Degree Programme in Data Analytics
Teachers
- Atte Reijonen
- Jarkko Ansamäki
Teacher in charge
Atte Reijonen
Groups
-
DAKV22SMData analytics, part-time
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?
Opiskelumateriaali
Web materials
Yksilölliset oppimisväylät
Individual learning tracks should always be discussed with the lecturers
TKI ja työelämäyhteistyö
The course may have assignments made for companies or assignments agreed individually with students.
Opiskelijan työmäärä
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)
Enrollment
07.11.2022 - 18.11.2022
Timing
11.01.2023 - 01.05.2023
Number of ECTS credits allocated
5 op
Mode of delivery
Contact teaching
Unit
Department of Business
Campus
Kouvola Campus
Teaching languages
- Finnish
Seats
20 - 40
Degree programmes
- Degree Programme in Data Analytics
Teachers
- Atte Reijonen
- Jarkko Ansamäki
Groups
-
DAKV21SPData-analytics, full-time studies
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?
Opiskelumateriaali
Web materials
Yksilölliset oppimisväylät
Individual learning tracks should always be discussed with the lecturers
TKI ja työelämäyhteistyö
The course may have assignments made for companies or assignments agreed individually with students.
Opiskelijan työmäärä
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)