This module will provide advanced data modelling skills, including topics such as generalised linear modelling, regularisation, and modelling using Bayesian inference. The module will embed consultancy skills and employability within this context of data modelling. Ethical implications will be discussed throughout.
Private Study: 170
Contact Hours: 30
Total: 200
Project plan and reflection from the point of view of client and consultant – 20%
Presentation by consultant to 'client' – 20%
Report on data modelling task – 60%
Reassessment methods
100% coursework.
The most up to date reading list for each module can be found on the university's reading list pages.
The intended subject specific learning outcomes
On successfully completing the module students will be able to:
1) Demonstrate a comprehensive understanding of advanced data modelling techniques such as generalised linear models, regularisation, and Bayesian modelling and apply them systematically.
2) Use R to apply the advanced data modelling techniques presented in the module.
3) Propose new hypotheses when presented with unseen complex datasets
4) Demonstrate originality in applying data modelling techniques to complex datasets.
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