GIS and digital applicationsLaajuus (5 cr)
Code: AT00CP52
Credits
5 op
Objective
The student is able to:
- identify the impacts and opportunities of digitalisation and industry 4.0 in the environmental sector
- understand the main principles of machine learning and programming
- explain applications of spatial data and use the QGIS spatial data programme (or a similar one)
- utilise various environmental databases
- recognise the risks of digitalisation and understand the significance of cyber security
Enrollment
20.11.2023 - 05.01.2024
Timing
01.01.2024 - 31.07.2024
Number of ECTS credits allocated
5 op
Virtual portion
5 op
Mode of delivery
Distance learning
Unit
Faculty of Technology (LAB)
Campus
E-campus, Lahti
Teaching languages
- Finnish
Degree programmes
- Bachelor’s Degree Programme in Environmental Engineering
- Bachelor's Degree Programme in Civil and Construction Engineering, Urban Planning (2022, 2023)
- Complementary competence and optional courses, Bachelors
Teachers
- Juha Poskela
- Sakari Autio
Scheduling groups
- Luennot 1 (Size: 500. Open UAS: 0.)
Groups
-
TLTIENTEC23KM
-
TLABTO23H
-
TLTIYKS23S
Small groups
- Lecture 1
Learning outcomes
The student is able to:
- identify the impacts and opportunities of digitalisation and industry 4.0 in the environmental sector
- understand the main principles of machine learning and programming
- explain applications of spatial data and use the QGIS spatial data programme (or a similar one)
- utilise various environmental databases
- recognise the risks of digitalisation and understand the significance of cyber security
Assessment scale
1-5
Enrollment
21.11.2022 - 08.01.2023
Timing
01.01.2023 - 31.07.2023
Number of ECTS credits allocated
5 op
Virtual portion
5 op
Mode of delivery
Distance learning
Unit
Faculty of Technology (LAB)
Campus
E-campus, Lahti
Teaching languages
- Finnish
Degree programmes
- Bachelor’s Degree Programme in Environmental Engineering
- Bachelor's Degree Programme in Civil and Construction Engineering, Urban Planning (2022, 2023)
Teachers
- Juha Poskela
- Sakari Autio
Scheduling groups
- Verkkoluento 1 (Size: 0. Open UAS: 0.)
Groups
-
TLTIYKS22S
-
TLTIENTEC22KM
Small groups
- Verkkoluento 1
Learning outcomes
The student is able to:
- identify the impacts and opportunities of digitalisation and industry 4.0 in the environmental sector
- understand the main principles of machine learning and programming
- explain applications of spatial data and use the QGIS spatial data programme (or a similar one)
- utilise various environmental databases
- recognise the risks of digitalisation and understand the significance of cyber security
Assessment scale
1-5