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Curricular information is subject to change
- acquiring basic scripting skills in Python for importing, manipulation, the analysis, and visualisation of different types of Earth-related datasets
- understanding the digital data workflow and basic elements of scripting
- Introduction to Python and automatic data import
- Importing of different data formats
- Loops and statements (making the tasks more efficient)
- Automatic data import from multiple data files
- Making sense of data (e.g. summarising, converting, synthesizing)
- Making a regular grid from irregularly sampled dataset (interpolation)
- Geodata visualisation (different plot types)
- Data regression
Student Effort Type | Hours |
---|---|
Lectures | 10 |
Practical | 15 |
Autonomous Student Learning | 25 |
Total | 50 |
Not applicable to this module.
Description | Timing | Component Scale | % of Final Grade | ||
---|---|---|---|---|---|
Continuous Assessment: Practical classroom-based work will be assessed twice throughout the course. | Throughout the Trimester | n/a | Standard conversion grade scale 40% | No | 65 |
Examination: The final exam will consist of a practical problem sheet. | Unspecified | Yes | Standard conversion grade scale 40% | No | 35 |
Resit In | Terminal Exam |
---|---|
Spring | No |
• Group/class feedback, post-assessment
Not yet recorded.