Undergraduate Course: Programming for Economics (ECNM10106)
Course Outline
| School | School of Economics |
College | College of Arts, Humanities and Social Sciences |
| Credit level (Normal year taken) | SCQF Level 10 (Year 3 Undergraduate) |
Availability | Available to all students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | Summary: This is a new course the details are not yet finalised. The information in this DRPS entry are therefore subject to change but is provided to give students an indicative overview of the content, delivery and assessment.
This course aims to enable students to learn the tools required to develop, simulate and explore economic models using a computer. It may also be of relevance to economics students who wish to develop coding skills.
The course is delivered through a combination of lectures and tutorials (and possibly computing laboratories). |
| Course description |
This course aims to enable students to learn the tools required to develop, simulate and explore economic models using a computer. It may also be of relevance to economics students who wish to develop coding skills.
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Information for Visiting Students
| Pre-requisites | None |
| High Demand Course? |
Yes |
Course Delivery Information
|
| Academic year 2022/23, Available to all students (SV1)
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Quota: None |
| Course Start |
Semester 2 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 20,
Supervised Practical/Workshop/Studio Hours 9,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
167 )
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
Group coursework with weekly submissions: 50%
Individual project: 50% |
| Feedback |
Not entered |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- A knowledge and understanding of key concepts, methods, issues and approaches in computational economics.
- Research and investigative skills such as problem framing and solving and the ability to assemble and evaluate complex evidence and arguments.
- Communication skills in order to critique, create and communicate understanding and to collaborate with and relate to others.
- Personal effectiveness through task-management, time-management, teamwork and group interaction, dealing with uncertainty and adapting to new situations, personal and intellectual autonomy through independent learning.
- Practical/technical skills such as, modelling skills (abstraction, logic, succinctness), qualitative and quantitative analysis and general IT literacy.
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Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | programming,coding |
Contacts
| Course organiser | |
Course secretary | |
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