MTHM611 - Topics in Environmental Intelligence (2023)
| MODULE TITLE | Topics in Environmental Intelligence | CREDIT VALUE | 15 |
|---|---|---|---|
| MODULE CODE | MTHM611 | MODULE CONVENER | Dr Oscar Rodriguez De Rivera Ortega (Coordinator) |
| DURATION: TERM | 1 | 2 | 3 |
|---|---|---|---|
| DURATION: WEEKS | 11 |
| Number of Students Taking Module (anticipated) | 30 |
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This module offers an insight to cutting-edge applications of Environmental Intelligence. You will be taught by world-leading experts from MetOffice and the University of Exeter in the application of Data Science and Artificial Intelligence to environmental data to address important questions related to meterorology, biodiversity and the environment. You will have the opportunity to explore a range of topics that address some of the most important challenges facing society today, including climate change, clean air, habitat and biodiversity loss, extreme weather events and the sustainable development goals. You will learn about new, and exciting techniques currently used by professionals in environmental data science. The choice of topics in any year may change to ensure that the content of the module reflects the rapid change in this exciting area.
The aims are to expose you to some recent developments in environmental intelligence; to allow you to study one or more advanced topics in some depth and to gain some insight into areas of postgraduate research in statistics. The choice of topics in any year may change to ensure that the content of the module reflects the rapid change in this exciting area.
On successful completion of this module you should be able to:
Module Specific Skills and Knowledge
1. Demonstrate an understanding of current developments in environmental intelligence.
2. Demonstrate an understanding of the strengths and limitations of different modelling approaches
3. Demonstrate the ability to apply advanced methodology across a variety of settings.
Discipline Specific Skills and Knowledge
4. Demonstrate an understanding the application of statistics, machine learning and AI in environmental challenges and real-world data.
5. Demonstrate the ability to self-learn further details of the methodology introduced within topics.
Personal and Key Transferable / Employment Skills and Knowledge
6. Demonstrate data analysis skills in complex topics
7. Demonstrate self-learning and making effective use of learning resources.
8. Communicate the results of a data analysis clearly and accurately, both in writing and verbally.
- Climate change
- Clean air
- Extreme weather
- Natural disasters
- Circular economy
- Sustainable development goals
- Clean/renewable energy
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Cloud computing
| Scheduled Learning & Teaching Activities | 30.00 | Guided Independent Study | 120.00 | Placement / Study Abroad | 0.00 |
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| Category | Hours of study time | Description |
| Scheduled Learning and Teaching Activities | 20 | Lectures |
| Scheduled Learning and Teaching Activities | 10 | Hands-on practical sessions |
| Guided Independent Study | 56 |
Self-study and background reading
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| Guided Independent Study | 64 | Assessed data analyses, report writing |
| Form of Assessment | Size of Assessment (e.g. duration/length) | ILOs Assessed | Feedback Method |
|---|---|---|---|
| Feedback on unassessed problem sheets and data analyses | 5 x 1 hour | 1-8 | Oral, in practical sessions |
| Coursework | 80 | Written Exams | 0 | Practical Exams | 20 |
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| Form of Assessment | % of Credit | Size of Assessment (e.g. duration/length) | ILOs Assessed | Feedback Method |
|---|---|---|---|---|
| Coursework – extended piece containing literature review, data analysis involving data collection, analysis and reporting | 80 | Max 10 pages (plus appendices) | 1-8 | Written and oral |
| Individual presentation | 20 | Max 10 minutes | 1-8 | Written and oral |
| Original Form of Assessment | Form of Re-assessment | ILOs Re-assessed | Time Scale for Re-assessment |
|---|---|---|---|
| Coursework – extended piece containing literature review, data analysis involving data collection, analysis and reporting | Coursework – extended piece containing literature review, data analysis involving data collection, analysis and reporting (80%) | 1-8 | Ref/def period |
| Individual presentation | Pre-recorded individual presentation (20%) | 1-8 | Ref/def period |
For referred candidates, the mark will be capped at 50%. For deferred candidates, the mark will be uncapped. Please refer to the TQA section on Referral/Deferral: https://as.exeter.ac.uk/academic-policy-standards/tqa-manual/aph/consequenceoffailure/
information that you are expected to consult. Further guidance will be provided by the Module Convener
The reading list will depend upon the module topic(s) offered and will be specified in detail by the lecturer(s) and agreed by the module coordinator for any particular year.
Reading list for this module:
There are currently no reading list entries found for this module.
| CREDIT VALUE | 15 | ECTS VALUE | 7.5 |
|---|---|---|---|
| PRE-REQUISITE MODULES | None |
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| CO-REQUISITE MODULES | None |
| NQF LEVEL (FHEQ) | 7 | AVAILABLE AS DISTANCE LEARNING | No |
|---|---|---|---|
| ORIGIN DATE | Wednesday 12 January 2022 | LAST REVISION DATE | Thursday 21 September 2023 |
| KEY WORDS SEARCH | Climate change; clean air; energy; environment |
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