Information Technology in Automation 3 (5 cr)

Code: TX00DT11-3004

General information

Enrollment: 28.11.2022 - 31.12.2022
Registration for the implementation has ended.

Timing: 13.03.2023 - 05.05.2023
Implementation has ended.

Number of ECTS credits allocated: 5 cr

Mode of delivery: On-campus

Unit: (2019-2024) School of Smart and Clean Solutions

Campus: Leiritie 1

Teaching languages: Finnish

Seats: 0 - 35

Degree programmes: Electrical and Automation Engineering

Teachers: Matti Välikylä

Teacher in charge: Raisa Kallio

Course: TX00DT11

Implementation has 7 reservations. Total duration of reservations is 26 h 15 min.

Time	Topic	Location
Mon 27.03.2023 time 17:00 - 20:45 (3 h 45 min)	Automaation tietotekniikka 3 TX00DT11-3004	Online
Mon 03.04.2023 time 17:00 - 20:45 (3 h 45 min)	Automaation tietotekniikka 3 TX00DT11-3004	Online
Thu 13.04.2023 time 17:00 - 20:45 (3 h 45 min)	Automaation tietotekniikka 3 TX00DT11-3004	Online
Mon 17.04.2023 time 17:00 - 20:45 (3 h 45 min)	Automaation tietotekniikka 3 TX00DT11-3004	Online
Thu 20.04.2023 time 17:00 - 20:45 (3 h 45 min)	Automaation tietotekniikka 3 TX00DT11-3004	Online
Mon 24.04.2023 time 17:00 - 20:45 (3 h 45 min)	Automaation tietotekniikka 3 TX00DT11-3004	Online
Wed 03.05.2023 time 17:00 - 20:45 (3 h 45 min)	Automaation tietotekniikka 3 TX00DT11-3004	Online

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

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.