MSc Data Science and Analytics

Year 1

Learning outcomes

On completion of the year/programme students should have provided evidence of being able to:
- Describe, perform and critically evaluate a range of strategies for analysing data, selecting suitable strategies for specific problems and communicating the appropriate results in a relevant way.
- Understand the difference of approach required between a traditional “simple random sample” and a “big data” (population) dataset and use this knowledge in devising analysis strategies.
- Carry out an analysis of structured and unstructured data, in either an open-ended (data mining) manner, or in relation to specific question.
- Analyse large datasets, including those which have more variables than observations.
- Describe, and implement various methods for classification, clustering and prediction, being able to critically evaluate and interpret any results in the context of the data.
- Demonstrate experience of using big data packages, and database skills.
- Describe issues associated with ethics and data governance, and evaluate their impact on data gathering and analysis.
- Demonstrate experience of data analytics in at least one specialism, for example: health, business, or environment.
- Demonstrate strong teamworking skill and the ability to communicate to both specialists and non-specialists.

Transferable (key) skills

Students will have had the opportunity to acquire the following abilities as defined in the modules specified for the programme:
- the skills necessary to undertake a higher research degree in data analytics, computer science, or statistics;
- evaluating the quality of data and selecting suitable methods of analysis;
- interpreting the pattern from data and decision making in complex data structure;
- setting targets for project work under supervision;
- independent learning and the ability to work in a way that ensures continuing professional development.

Assessment

Achievement for the degree of Master (taught programme) will be assessed by a variety of methods in accordance with the learning outcomes of the modules specified for the year/programme and will involve the achievement of the students in:
- evidencing an ability to select and conduct appropriate data analyses;
- demonstrating the ability to apply breadth and/or depth of knowledge to analysing data;
- drawing an analytic perspective on a particular area of study;
- evaluating and criticising existing analyses and conclusions;
- make reasoned judgements whilst understanding the limitations on judgements made in the absence of complete data.