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.



The programme provides a balanced route to learning through a blend of academic study and lab sessions, with a heavy focus on practical engagement with industry. 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.

Core Modules

Data Analytics Fundamentals (20 credits)

Database & Programming Fundamentals (20 credits)

Data Mining (20 credits)

Machine Learning (20 credits)

Frontiers in Analytics (20 credits)

Analytics in Action (20 credits)

Individual Industry Based Project (60 credits)

Entrance requirements

Graduate

Normally a 2.1 Honours degree in Mathematics, Statistics, Computer Science, Computer Applications, or a closely related discipline, or equivalent qualification acceptable to the University.



Applicants with a minimum 2.2 Honours degree in a cognate discipline, a 2.1 Honours degree in a non-cognate discipline, or who have not yet completed their degree, will be considered on a case-by-case basis.



All applicants will be expected to have significant mathematical ability for this course.



Applications may be considered from those who do not meet the above requirements but can provide evidence of recent relevant technical experience in industry, for example, in programming, data analytics, or AI development. The University's Recognition of Prior Learning Policy provides guidance on the assessment of experiential learning (RPEL).



International Students

Our country/region pages include information on entry requirements, tuition fees, scholarships, student profiles, upcoming events and contacts for your country/region at https://www.qub.ac.uk/Study/international-students/your-country/



English Language Requirements

Evidence of an IELTS* score of 7.0, with not less than 6.0 in any component, or an equivalent qualification acceptable to the University is required (*taken within the last 2 years).



International students wishing to apply to Queen's University Belfast (and for whom English is not their first language), must be able to demonstrate their proficiency in English in order to benefit fully from their course of study or research. Non-EEA nationals must also satisfy UK Visas and Immigration (UKVI) immigration requirements for English language for visa purposes.



For more information on English Language requirements for EEA and non-EEA nationals see: www.qub.ac.uk/EnglishLanguageReqs.



If you need to improve your English language skills before you enter this degree programme, INTO Queen's University Belfast offers a range of English language courses. These intensive and flexible courses are designed to improve your English ability for admission to this degree.

Please note the closing date for MSc Data Analytics for September 2026 entry is 30 June. Applications received after this date and time will be regarded as LATE and will be considered only if vacancies exist when all applications received by this date and time have been processed.



Please note: a deposit will be required to secure a place.

Coursework

Written examination

Project dissertation

1 year (Full-time), 2 years (Part-time).

Entry Year: Academic Year 2026/27

Career Prospects

Industry forecasts indicate that Data Analytics is a growing field internationally, with job opportunities set to increase exponentially predicting growths of 160% between 2013 and 2020 (eSkills report, Big Data Analytics 2013-2020). There is a current shortage in qualified staff for these roles, which is also the case in Northern Ireland where there have been a number of recent investments and expansions in the Data Analytics sector.



The course is designed to meet the needs of Industry where graduates have the right combination of the skills and expertise in both computer science, mathematics and statistics along with the experience they gain in their individual industry based project to be highly sought after for employment.



Queen's postgraduates reap exceptional benefits. Unique initiatives, such as the leadership and executive programmes alongside sterling integration with business experts helps our students gain key leadership positions both nationally and internationally.

http://www.qub.ac.uk/directorates/sgc/careers/