Implementing IoT PipelineLaajuus (15 cr)
Code: AT00CK36
Credits
15 op
Teaching language
- English
Objective
The student is able to
- create a scalable restful API-services for IoT data
- implement ML and AI operations also in edge devices
- use appropriate databases to store IoT data in the platform
- work as a team leader in an ICT project and a member in a multidisciplinary project
Enrollment
20.11.2024 - 03.01.2025
Timing
01.01.2025 - 30.06.2025
Number of ECTS credits allocated
15 op
Mode of delivery
Contact teaching
Unit
Faculty of Technology (LAB)
Campus
Lappeenranta Campus
Teaching languages
- English
Degree programmes
- Bachelor's Degree Programme in Industrial Information Technology
Teachers
- Mira Vorne
- Jyrki Antikainen
Scheduling groups
- Luennot 1 (Size: 500. Open UAS: 0.)
Groups
-
TLPRIIT23S
-
TLPRIIT22S
Small groups
- Lecture 1
Learning outcomes
The student is able to
- create a scalable restful API-services for IoT data
- implement ML and AI operations also in edge devices
- use appropriate databases to store IoT data in the platform
- work as a team leader in an ICT project and a member in a multidisciplinary project
Assessment scale
1-5
Enrollment
01.12.2022 - 04.01.2023
Timing
09.01.2023 - 28.04.2023
Number of ECTS credits allocated
15 op
Mode of delivery
Contact teaching
Unit
Faculty of Technology (LAB)
Campus
Lappeenranta Campus
Teaching languages
- English
Degree programmes
- Bachelor's Degree Programme in Industrial Information Technology
Teachers
- LAB_virtuaalihenkilö_TVT_01 Virtuaaliopettaja (LAB)
- Karri Miettinen
- Jyrki Antikainen
Scheduling groups
- Luennot 1 (Size: 500. Open UAS: 0.)
Groups
-
TLPRIIT21S
Small groups
- Luennot 1
Learning outcomes
The student is able to
- create a scalable restful API-services for IoT data
- implement ML and AI operations also in edge devices
- use appropriate databases to store IoT data in the platform
- work as a team leader in an ICT project and a member in a multidisciplinary project
Assessment scale
1-5