Data and RDI as a success factorsLaajuus (15 op)
Tunnus: AT00CK39
Laajuus
15 op
Opetuskieli
- englanti
Osaamistavoitteet
The student is able to
- utilize modern analyzing, ML, and AI tools to solve engineering problems
- visualize and report the processed data in a suitable way using modern tools
- create a data visualization using HTML and backend services
- understand digital twin operation principles
- understand the importance and principles of leading, law, marketing and business economy as a part of a company operations
- write a technical report and represent it
Ilmoittautumisaika
15.05.2023 - 01.09.2023
Ajoitus
01.08.2023 - 31.12.2023
Opintopistemäärä
15 op
Toteutustapa
Lähiopetus
Yksikkö
Teknologia (LAB)
Toimipiste
Lappeenrannan kampus
Opetuskielet
- Englanti
Koulutus
- Bachelor's Degree Programme in Industrial Information Technology
Opettaja
- Karri Miettinen
- Antti Jokinen
- Jyrki Antikainen
Opetusryhmät
- Luennot (Koko: 0. Avoin AMK: 0.)
Ryhmät
-
TLPRIIT21SBachelor's Degree Programme in Industrial Information Technology 21S Lappeenranta
-
TLPRIIT22SBachelor's Degree Programme in Industrial Information Technology 22S Lappeenranta
Pienryhmät
- Luennot
Osaamistavoitteet
The student is able to
- utilize modern analyzing, ML, and AI tools to solve engineering problems
- visualize and report the processed data in a suitable way using modern tools
- create a data visualization using HTML and backend services
- understand digital twin operation principles
- understand the importance and principles of leading, law, marketing and business economy as a part of a company operations
- write a technical report and represent it
Toteutustapa ja opetusmenetelmät
Course consists of many individual assignments and some group assignments. Some of the assignments requires attending on the premises.
Ajoitus ja läsnäolo
Attending classes is required according to the schedules in the Time-edit.
Oppimateriaali ja suositeltava kirjallisuus
Material is shared in the Moodle platform and some presented during the lessons.
Toteutuksen valinnaiset suoritustavat
None
Työelämäyhteistyö
None
Uusintamahdollisuudet
The course grading is based on assigments given during the classes and some group assignments.
In case there are exams during the course, then the LAB's rules and regulations are applied to the exam (two or more changes to take a replacement exam.)
Oppimisympäristö
Lappeenranta Campus & Moodle
Opiskelijan ajankäyttö ja kuormitus
The scope of the course is 15 credits, which corresponds to an average of 412 hours of studying, containing the scheduled lectures and self-studying.
Sisältö
Digital Twin
AI/ML tools
Leading Law, Marketing and business economy
Lisätietoja opiskelijalle: mm. edeltävä osaaminen
Object-oriented programming
Arviointimenetelmät
Assessment will be based on exercises, individual and team assignments and possible exams.
Student activity will affect grading.
Arviointiasteikko
1-5
Hylätty (0)
Student doesn't reach the course's competence goals.
Arviointikriteerit: taso 1: (arviointiasteikko 1-5)
Understands the course topics and can contribute to RDI processes.
Arviointikriteerit: taso 3 (arviointiasteikko 1-5)
Can utilize modern analyzing, ML and AI tools to solve engineering problems. Is able to visualize data using modern web development related tools and understands the importance of the leading, law, marketing and business economy as a part of a company operations.
Arviointikriteerit: taso 5 (arviointiasteikko 1-5)
Rules the level 3 matters and can take leading role in RDI processes