MAEN4300 Strømningsteknikk og numeriske beregninger Emneplan

No formal requirements over and above the admission requirements.

None.

Upon completing the course, the student will have the following outcomes.

Knowledge:

Upon successfully completion of the course, the student:

• has advanced knowledge of spatial data handling
• has advanced knowledge of spatial analysis techniques, including a good understanding of predictive algorithms and geo-statistics, relevant to spatial & urban analysis
• has advanced knowledge of how to implement artificial intelligence (AI) and machine learning (ML) in urban analytics
• has advanced knowledge of data analysis (analytical techniques) and visualization using geospatial tools, primarily within urban analytics

Skills:

Upon successfully completion of the course, the student:

• is an experienced user and have a broad understanding of Geographical Information Systems (GIS)/Geospatial tools as well as of methods and theory in spatial analysis
• has hands-on experience with relevant techniques, algorithms and scripting in GIS/Geospatial tools
• has hand-on experience with relevant programming and scripting environments for use in data science, especially within urban analytics and visualization of urban data
• has knowledge of how to test and implement urban theory using spatial data and urban analytics

General competence:

Upon successfully completion of the course, the student:

• has broad overview of both the challenges and the tools of urban analytics
• is able to design approaches and utilize tools for analysing and visualizing urban data
• is able to extend his/her knowledge and skills in programming/scripting, analysing, managing and visualizing data both in urban analytics and in other area
• is able to use a relevant theoretical framework in applied studies
• can create and communicate findings in ways that are relevant to stakeholders

This course features 10 weeks lectures with 10 parallel lab sessions to provide theoretical content and preliminary hands-on experience. The lab sessions will be preceded with one or two weeks of (primarily technical) preparatory sessions.

All individual assignments must be approved.

Lab assignments must be handed in

Students who fail to meet the coursework requirements can be given up to one re-submission opportunity.

1) A final project report prepared individually or in groups of 2 (or more) students, approx. 15 - 20 pages (excluding appendices, including code and calculations), weighted 60%.

2) Oral presentation and examination (individually or in the same groups as for the written part) of the project report weighted 40%.

All assessment parts must be awarded a pass grade (E or better) to pass the course.

Assessment parts: 1) can be appealed, 2) cannot be appealed

1) All aids are permitted, as long as the rules for source referencing are complied with.

2) None

Graded scale A-F.

1) Two internal examiners.

External examiners are used regularly.

John Östh; Email: john.osth@oslomet.no