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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
  • TLPRIIT21S
    Bachelor's Degree Programme in Industrial Information Technology 21S Lappeenranta
  • TLPRIIT22S
    Bachelor'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