This course constitutes the dissertation phase of the MSc programmes in Data Analytics (ODL). It gives students with an opportunity to critically reflect upon their own professional practice, taking into account both the knowledge acquired on the MSc programme and the relevant literature.

None.

Data Analytics Project (ODL)

20% presentation and mini viva, 80% final submission of a portfolio, which includes a dissertation

This course aims to provide students with an opportunity to critically reflect upon their own professional practice. It is intended that students describe substantial project work they have already carried out themselves in the area of data analytics and construct and discuss what would constitute best practice in such situations, taking into account both the knowledge acquired on the MSc programme and the relevant literature.

By the end of this course students will be able to: 

1. critically reflect upon their own professional practice;

2. integrate and consolidate the knowledge and skills they have gained from other components of their degree programme;

3. critique a plan for a statistical analysis or other data-analytic work, as well as its execution

4. investigate and discuss the merits and risks involved in using different approaches to tackle a data analytics problem;

5. critically evaluate the relevant literature and software and make connections between them and the project(s) to be investigated;

6. assemble and discuss best practice guidelines for specific data analysis problems, taking into account technical and ethical issues as well as organisational and other constraints;

7. present key results and conclusions to both technical and non-technical audiences; and  

8. synthesise and write up the lessons from the enquiry highlighting key lessons learned and their implications.

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.