- Dr Kevin (Yong Kyu) Gam
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Curricular information is subject to change
On successful completion of this module students should be able to:
1. Explain how different statistical techniques can be applied to the modelling and monitoring of SDGs.
2. Demonstrate a comprehensive understanding of the practical implementation of green
data science projects.
3. Critically evaluate data completeness and coverage on SDGs.
4. Implement data processes and robustness checks for Anti-Green-Washing.
5. Critically assess whether and how new financial technologies may be applied to the field of sustainable development.
|Student Effort Type||Hours|
|Autonomous Student Learning||
Not applicable to this module.
|Description||Timing||Component Scale||% of Final Grade|
|Group Project: Students will work on a small group research project and presentation on assessing the accuracy and completeness of GHG emission claims of companies.||Week 4||n/a||Graded||No||
|Assignment: Online python introductory course||Throughout the Trimester||n/a||Pass/Fail Grade Scale||No||
|Group Project: Group data project||Week 11||n/a||Graded||No||
|Essay: 3,000 word essay on a current topic in green data science||Week 7||n/a||Graded||No||
Not yet recorded
|Dr Theodor Cojoianu||Lecturer / Co-Lecturer|