Programplaner og emneplaner - Student
MABY5345 Water Infrastructures and Sensor Networks Course description
- Course name in Norwegian
- Water Infrastructures and Sensor Networks
- Study programme
-
Master’s Programme in Civil Engineering
- Weight
- 10.0 ECTS
- Year of study
- 2025/2026
- Programme description
- Course history
-
Introduction
No formal requirements over and above the admission requirements.
Required preliminary courses
After completing the course, the student is expected to have achieved the following learning outcomes defined in terms of knowledge, skills and general competence:
Knowledge:
The student has advanced knowledge of:
- research methods, especially in engineering research
- statistical and analytical techniques, including knowledge of the most common libraries and tools used in statistical analysis and visualisation of the results
- designing experiments, preparing data and interpreting analysis results
- how relevant statistical and computational techniques relate to each other and where they are used
Skills:
The student has:
- required skills in setting up sound experiments, hypotheses and research questions, and in finding and preparing relevant data
- required skills in identifying which statistical and analytical techniques are to be used and how and where they should be used
- hands-on experience with some of the most common computational techniques and libraries as well as related tools for statistical analysis
- hands-on experience with relevant tools for use in analyses
General competence:
The student:
- has broad overview of the computational tools and techniques used in analysis and engineering research, including statistical techniques and techniques related to data science and machine learning
- has an overview of the terminology related to statistical analysis and data science.
- is able to design experiments for successful engineering research, analyses and critical interpretation of results
- can extend his/her knowledge and skills in programming/scripting, analysing, managing and visualizing data
Learning outcomes
Grade scale A-F
Teaching and learning methods
Students are required to complete one mandatory project assignment in allocated time and get it approved. Students who fail to meet the coursework requirements can be given up to one re-submission opportunity. (more details in Canvas).
Course requirements
1) One internal examiner,
2) Two internal examiners
External examiners are used regularly.
Assessment
1) All aids are permitted, as long as the rules for source referencing are complied with.
2) None
Permitted exam materials and equipment
Graded scale A-F.
Grading scale
Graded scale A-F
Examiners
Two internal examiners.
External examiners are used regularly.
Course contact person
Lena Magnusson Turner
Overlapping courses
None