Only available to students on an Integrated Masters in Data Science or Data Science with Intercalated Year.
To allow students to synthesize, apply and extend the knowledge and skills developed during the taught component of their degree and to demonstrate mastery of some elements of Data Science.
Principal Learning Outcomes:
To demonstrate in-depth comprehension of an aspect of Data Science. The focus of a typical dissertation may be (this list is illustrative, not exhaustive)
- To implement and provide a critical analysis of a method of collection of methods for performing a particular task.
- To synthesize an area of research within Data Science, extending knowledge where possible, demonstrating mastery of the material and expanding on arguments given in the literature
- To apply Data Science Knowledge and skills to answer a research question relating to a real data set.
Each student will be allocated an individual dissertation supervisor in Statistics or Computer Science. The dissertation supervision will consist of individual supervisory meetings accompanied by independent research and the writing of the dissertation. The topic of the dissertation can be any topic within the field of data science as jointly agreed by the student and their supervisor.