Data Analytics

Overview

Data Analytics is an exciting field of rapid developments. Data is everywhere and continuing to grow massively, creating huge growth in demand for qualified experts to be able to extract the real benefit from the data.

The role of a data scientist is highly diverse overlapping many areas from computer science, to the fundamentals of mathematics, statistics, modelling and analytics while also requiring the right skills to be able to see the detail, solve the problem (having specified the problem!), and communicate effectively the findings to colleagues to empower them to make decisions.

The diversity of data analytics opens up many job opportunities from working in software companies, healthcare, banking, insurance, policing, tech companies to applying your knowledge to intelligent buildings and behaviour analytics of customers.

In the first and second semesters, you will study 6 modules full-time which include opportunities for blended and collaborative learning. In the third semester you will undertake a significant industry based project.

Industry Links

Special features of the course include the Analytics in Action module and the commitment of industry to provide real data for “Analytathons” and projects. The module offers real world examples of data analytics presented by the industry experts working alongside the academics who will provide the theory, and the unique provision of this course across many academic disciplines in the University.

World Class Facilities

The Frontiers in Analytics module shows off some of latest state-of-the-art techniques analytics in particular in Visual Analytics and Behavioural Analytics.

Student Experience

This Data Analytics programme at Queen's University Belfast is unique having been developed from engagement with industry rather than the traditional academic subject areas. 

The key core skills that a data scientist needs have been clearly defined and forms the basis for the course. As a result, there are no optional modules or choice as it is essential that in order to produce the “all rounded” data scientist that all these skills are packaged into each individual.