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Information Technology in Automation 3 (5 cr)

Code: TX00DT11-3006

General information


Enrollment
01.05.2024 - 31.05.2024
Registration for the implementation has ended.
Timing
21.10.2024 - 13.12.2024
Implementation has ended.
Number of ECTS credits allocated
5 cr
Local portion
5 cr
Mode of delivery
On-campus
Unit
(2019-2024) Team Smart
Campus
Leiritie 1
Teaching languages
Finnish
Seats
20 - 50
Degree programmes
Electrical and Automation Engineering
Teachers
Matti Välikylä
Teacher in charge
Raisa Kallio
Groups
SA21S
Automaatiotekniikan pääaine, syksyllä 2021 aloittaneet päiväopiskelijat
Course
TX00DT11

Implementation has 16 reservations. Total duration of reservations is 46 h 0 min.

Time Topic Location
Thu 24.10.2024 time 11:00 - 14:00
(3 h 0 min)
Automaation tietotekniikka 3 TX00DT11-3006
MMB330 IT-Tila
Fri 25.10.2024 time 09:00 - 12:00
(3 h 0 min)
Automaation tietotekniikka 3 TX00DT11-3006
MMC376.2 Automaatiolaboratorio 2, Automaatioprosessit
Thu 31.10.2024 time 11:00 - 14:00
(3 h 0 min)
Automaation tietotekniikka 3 TX00DT11-3006
MMB330 IT-Tila
Fri 01.11.2024 time 09:00 - 12:00
(3 h 0 min)
Automaation tietotekniikka 3 TX00DT11-3006
MMC376.2 Automaatiolaboratorio 2, Automaatioprosessit
Thu 07.11.2024 time 11:00 - 14:00
(3 h 0 min)
Automaation tietotekniikka 3 TX00DT11-3006
MMB330 IT-Tila
Fri 08.11.2024 time 09:00 - 12:00
(3 h 0 min)
Automaation tietotekniikka 3 TX00DT11-3006
MMC376.2 Automaatiolaboratorio 2, Automaatioprosessit
Thu 14.11.2024 time 11:00 - 14:00
(3 h 0 min)
Automaation tietotekniikka 3 TX00DT11-3006
MMB330 IT-Tila
Fri 15.11.2024 time 09:00 - 12:00
(3 h 0 min)
Automaation tietotekniikka 3 TX00DT11-3006
MMC376.2 Automaatiolaboratorio 2, Automaatioprosessit
Wed 20.11.2024 time 08:00 - 11:00
(3 h 0 min)
Automaation tietotekniikka 3 TX00DT11-3006
MMC376.2 Automaatiolaboratorio 2, Automaatioprosessit
Thu 21.11.2024 time 10:00 - 12:00
(2 h 0 min)
Automaation tietotekniikka 3 TX00DT11-3006
MMC376.1 Automaatiolaboratorio 1, Ryhmätyötila
Thu 28.11.2024 time 11:00 - 14:00
(3 h 0 min)
Automaation tietotekniikka 3 TX00DT11-3006
MMB330 IT-Tila
Fri 29.11.2024 time 09:00 - 12:00
(3 h 0 min)
Automaation tietotekniikka 3 TX00DT11-3006
MMC376.2 Automaatiolaboratorio 2, Automaatioprosessit
Thu 05.12.2024 time 09:00 - 11:00
(2 h 0 min)
Automaation tietotekniikka 3 TX00DT11-3006
MMC376.2 Automaatiolaboratorio 2, Automaatioprosessit
Thu 05.12.2024 time 11:00 - 14:00
(3 h 0 min)
Automaation tietotekniikka 3 TX00DT11-3006
MMB330 IT-Tila
Thu 12.12.2024 time 11:00 - 14:00
(3 h 0 min)
Automaation tietotekniikka 3 TX00DT11-3006
MMC376.1 Automaatiolaboratorio 1, Ryhmätyötila
Fri 13.12.2024 time 09:00 - 12:00
(3 h 0 min)
Automaation tietotekniikka 3 TX00DT11-3006
MMC376.2 Automaatiolaboratorio 2, Automaatioprosessit
Changes to reservations may be possible.

Objective

The student can name the software technology in various application objects in automation, implement small software projects in automation, as well as to apply software engineering methods in software projects and plan to define and automation software projects.
- Students are able to explain the significance and application of different cloud services and Big Data in industrial automation.

Content

1. Automation software engineering
2. Cloud services and Big Data

Location and time

Lukujärjestyksen mukaan

Materials

Tarvittavan materiaalin ääreen ohjataan kurssin aikana.

Teaching methods

Excercises
Excercises in groups

Employer connections

Mahdollisuuksien mukaan opiskelijan itse hankkiman kumppanin kanssa. Sovittavissa erikseen.

Completion alternatives

Mahdollisuus yksilölliseen suoritustapaan erikseen sovitulla tavalla

Student workload

Ohjattua toimintaa lukujärjestyksen mukaan 2x3 tuntia viikossa
Omatoimista työtä keskimäärin noin 10-11 tuntia viikossa.

YHTEENSÄ 135 tuntia (5 op)

Evaluation scale

0-5

Assessment criteria, satisfactory (1)

The student has achieved the course objectives fairly. The student will be able to identify, define and use the course subject area’s concepts and models. The student understands the criteria and principles of the expertise development. The student has completed the required learning exercises in minimum requirement level. His/her competences have developed in a way that he/she may complete the remaining studies in electrical engineering and automation technology and finally work in a suitable job position related to this field.

Assessment criteria, good (3)

The student has achieved the course objectives well, even though the knowledge and skills need improvement on some areas. The student has completed the required learning exercises in good or satisfactory level. The student is able to define the course concepts and models and is able to justify the analysis. The student is able to apply their knowledge in study and work situations. The student understands the importance of expertise in the field of electrical engineering and automation technology and is able to analyze his/her own expertise.

Assessment criteria, excellent (5)

The student has achieved the objectives of the course with excellent marks. The student master commendably the course subject area’s concepts and models. The student has completed the required learning exercises in good or excellent level. The student is able to make justified and fluent analysis and to present concrete development measures. The student is well prepared to apply their knowledge study and work situations. Students are able to analyze the expertise in electrical engineering and automation technology and the evolvement of their own expertise.

Assessment criteria, approved/failed

The student has achieved the course objectives fairly. The student will be able to identify, define and use the course subject area’s concepts and models. The student understands the criteria and principles of the expertise development. The student has completed the required learning exercises in minimum requirement level. His/her competences have developed in a way that he/she may complete the remaining studies in electrical engineering and automation technology and finally work in a suitable job position related to this field.

Assessment methods and criteria

The performance is continuously assessed and different activities will cumulate points from the first week onwards.

Points | Grade
0 | 0
17 | 1
24 | 2
30 | 3
37 | 4
44+ | 5

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