Digitaaliset kaksosetLaajuus (5 op)
Tunnus: R504D81
Laajuus
5 op
Ilmoittautumisaika
02.10.2023 - 31.01.2024
Ajoitus
01.02.2024 - 10.05.2024
Laajuus
5 op
Toteutustapa
Lähiopetus
Yksikkö
Insinöörikoulutus, tieto- ja viestintätekniikka
Opetuskielet
- Englanti
- Suomi
Paikat
0 - 30
Opettaja
- Toni Westerlund
Vastuuhenkilö
Toni Westerlund
Opiskelijaryhmät
-
R54D21SBachelor of Engineering, Machine Learning and Data Engineering (full time studies), 2021
Aika ja paikka
Education according to the timetable at the Rantavitika campus, Jokiväylä 11, in the spring semester 2023
Oppimateriaalit
Lecture material, examples and exercises. In the Moodle workspace, a link to the shared Drive/OneDrive material directory.
Opetusmenetelmät
36 hours of classroom teaching and exercises, independent study, 101.5 hours of practical work.
Doing exercises in your own time in addition to lessons is essential if you want to achieve the skills and professional qualifications required in working life.
Tenttien ajankohdat ja uusintamahdollisuudet
There is no exam in the course. Competence is demonstrated through practice tasks.
Toteutuksen valinnaiset suoritustavat
There is no exam in the course. Returnable practice tasks or a project of a similar size, which can be used to demonstrate competence in the subject area being discussed.
Sisällön jaksotus
Unity / Unreal Engine
- Simple digital Twins that can be used to represent data
- Two-way digital Twins, which can be used to control the equipment.
- Two-way digital twins that also enable simulations
Lisätietoja opiskelijoille
We use game engines and game technology in the Study Course. Completing the course requires hardware that enables unreal/unity game engine development. Students have access to the school's computers and the opportunity to use the Citrix service
Arviointiasteikko
H-5
Arviointimenetelmät ja arvioinnin perusteet
The assessment is based on the test completed in the study course (demonstrating competence) and the study course's practice assignments.