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MSc|Postgraduate Taught

Data Analytics

Entry year
2025/26
Entry requirements
2.1 in cognate degree (2.2 in cognate or 2.1 in non-cognate requires successful completion of aptitude test)
Duration
1 year (Full-time)
2 years (Part-time)
Places available
68 (Full Time)
(Part Time)

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.

PLEASE NOTE:
You may be required to sit an online aptitude test. The test has been created by the MSc Data Analytics lecturers, and is based on the Cambridge Assessment TMUA; you can find more information on the TMUA, as well as practice papers should you wish to try them, here: https://www.admissionstesting.org/for-test-takers/test-of-mathematics-for-university-admission/preparation/

Aptitude Tests will be held on the dates below 3-4pm (GMT) for 24/25.

10 October 2024
7 November
5 December
9 & 23 January 2025
6 & 20 February
6 & 20 March
10 April
1 & 15 & 29 May
12 & 26 June

**Applicants must attend their allocated session as notified by the school. Please ensure that you check your junk email folders regularly for communications from the School regarding your application/aptitude test. Additional aptitude tests may be scheduled if required.


In addition, a deposit will be required to secure a place. Please see below the deposit deadline schedule:

1. Offer received by 31 December 2023 deposit deadline 31 January 2024
2. Offer received by 31 January 2024 deposit deadline 28 February 2024
3. Offer received by 28 February 2024 deposit deadline 31 March 2024
4. Offer received by 31 March 2024 deposit deadline 30 April 2024

Please note that applicants may be required to undertake an aptitude test. Decisions will be issued within 10 working days from the date of the aptitude test. In addition, a deposit will be required to secure a place.

Data Analytics highlights

Student Experience

This course 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.

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.

Course Structure

Modules are taught in block delivery mode where each module runs in blocks of 4 weeks in a sequential manner where at any one time, the student is working on only one module.

Week 1 requires students to carry out background reading and preparation work in advance of
Week 2 requires students to attend lectures/labs Monday – Friday 9am-5pm
Week 3 is normally reserved for project work and helpdesk sessions
Week 4 is normally reserved for additional helpdesk sessions and assessments

Full-time students are expected to be present at Queen’s during each Teaching Week (week 2) of each module as well as Assessment (normally week 4).

In the four week duration of a module, there will be an intensive teaching week where the schedule will consists of 9am-5pm with approximately equal numbers of lectures (in the mornings) and labs (in the afternoons).

Part time students, please note that although the course is part time in terms of number of modules taken each year, the modules themselves are still taught full time in block delivery mode as detailed above.

Course Details

The aim of the programme is to offer a multi-disciplinary education in data analytics that prepares graduates with key knowledge, skills and competencies necessary for employment in analytics and data science positions. In particular, the programme aims to provide students with:

Comprehensive knowledge and understanding of the fundamental principles of statistics and computer science that underpin analytics.

Advanced knowledge and practical skills in the theory and practice of analytics.

The necessary skills, tools and techniques needed to embark on careers in data analytics and data science.

Skills in a range of practices, processes, tools and methods applicable to analytics in commercial and research contexts.

Timely exposure to, and practical experience in, a range of current software packages and emerging new applications of analytics.

Opportunities for the development of practical skills in a commercial context.

Modules

Data Analytics Fundamentals
Databases and Programming Fundamentals
Data Mining
Machine Learning
Frontiers in Data Analytics
Analytics in Action
Individual Industry Based Project

Indicative number of modules per semester: 3

People teaching you

Course Director

School of Maths and Physics
Email: mp.pgt@qub.ac.uk

Learning and Teaching

Students must complete modules in block delivery mode where each module runs in blocks of 4 weeks in a sequential manner where at any one time, the student is working on only one module. Week 1 of block delivery mode requires students to carry out background reading and preparation work in advance of week 2 of each block which requires students to attend lectures/labs Monday –Friday 9am-5pm.

Weeks 3 and 4 of each block are for project and coursework. Full-time students are expected to be present at Queen’s during weeks 2, 6, 10, 14, 18 and 22 of the academic year.

In the four week duration of a module, there will be an intensive teaching week where the schedule will consists of 9am-5pm with approximately equal numbers of lectures (in the mornings) and labs (in the afternoons).

Part time students, please note that although the course is part time in terms of number of modules taken each year, the modules themselves are still taught full time in block delivery mode as detailed above.

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Assessment

Assessments associated with the course are outlined below:

  • Coursework
  • Written examination
  • Project dissertation
  • Presentations

What our academics say

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Modules

Modules

The information below is intended as an example only, featuring module details for the current year of study (2024/25). Modules are reviewed on an annual basis and may be subject to future changes – revised details will be published through Programme Specifications ahead of each academic year.

  • Year 1

    Core Modules

    Data Mining (20 credits)
    Machine Learning (20 credits)
    Analytics in Action (20 credits)

Entrance requirements

Graduate

Normally a 2.1 Honours degree in Mathematics, Statistics, or Computer Science 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 required to pass an aptitude test.

Please note the closing date for MSc Data Analytics for September 2025 entry is 31 March 2025 at 4pm. 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.

We encourage applicants to apply as early as possible. In the event that any programme receives a high number of applications, the University reserves the right to close the application portal earlier than 31 March 2025 deadline. Notifications to this effect will appear on the application portal against the programme application page.

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

International Students

Our country/region pages include information on entry requirements, tuition fees, scholarships, student profiles, upcoming events and contacts for your country/region. Use the dropdown list below for specific information for your country/region.

English Language Requirements

Evidence of an IELTS* score of 6.5, with not less than 5.5 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.

  • Academic English: an intensive English language and study skills course for successful university study at degree level
  • Pre-sessional English: a short intensive academic English course for students starting a degree programme at Queen's University Belfast and who need to improve their English.

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Careers

Career Prospects

Introduction

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/

Graduate Plus/Future Ready Award for extra-curricular skills

In addition to your degree programme, at Queen's you can have the opportunity to gain wider life, academic and employability skills. For example, placements, voluntary work, clubs, societies, sports and lots more. So not only do you graduate with a degree recognised from a world leading university, you'll have practical national and international experience plus a wider exposure to life overall. We call this Graduate Plus/Future Ready Award. It's what makes studying at Queen's University Belfast special.

Tuition Fees

Northern Ireland (NI) 1 £8,800
Republic of Ireland (ROI) 2 £8,800
England, Scotland or Wales (GB) 1 £9,250
EU Other 3 £25,800
International £25,800

1EU citizens in the EU Settlement Scheme, with settled status, will be charged the NI or GB tuition fee based on where they are ordinarily resident. Students who are ROI nationals resident in GB will be charged the GB fee.

2 EU students who are ROI nationals resident in ROI are eligible for NI tuition fees.

3 EU Other students (excludes Republic of Ireland nationals living in GB, NI or ROI) are charged tuition fees in line with international fees.

All tuition fees quoted relate to a single year of study unless stated otherwise. Tuition fees will be subject to an annual inflationary increase, unless explicitly stated otherwise.

More information on postgraduate tuition fees.

Additional course costs

Terms and Conditions for Postgraduate applications:

1.1  Due to high demand, there is a deadline for applications. 
1.2  You will be required to pay a deposit to secure your place on the course.
1.3  This condition of offer is in addition to any academic or English language requirements.

Read the full terms and conditions at the link below:
https://www.qub.ac.uk/Study/EPS/terms-and-conditions/

All Students

Depending on the programme of study, there may be extra costs which are not covered by tuition fees, which students will need to consider when planning their studies.

Students can borrow books and access online learning resources from any Queen's library. If students wish to purchase recommended texts, rather than borrow them from the University Library, prices per text can range from £30 to £100. Students should also budget between £30 to £75 per year for photocopying, memory sticks and printing charges.

Students undertaking a period of work placement or study abroad, as either a compulsory or optional part of their programme, should be aware that they will have to fund additional travel and living costs.

If a programme includes a major project or dissertation, there may be costs associated with transport, accommodation and/or materials. The amount will depend on the project chosen. There may also be additional costs for printing and binding.

Students may wish to consider purchasing an electronic device; costs will vary depending on the specification of the model chosen.

There are also additional charges for graduation ceremonies, examination resits and library fines.

How do I fund my study?

The Department for the Economy will provide a tuition fee loan of up to £6,500 per NI / EU student for postgraduate study. Tuition fee loan information.

A postgraduate loans system in the UK offers government-backed student loans of up to £11,836 for taught and research Masters courses in all subject areas (excluding Initial Teacher Education/PGCE, where undergraduate student finance is available). Criteria, eligibility, repayment and application information are available on the UK government website.

More information on funding options and financial assistance - please check this link regularly, even after you have submitted an application, as new scholarships may become available to you.

International Scholarships

Information on scholarships for international students, is available at www.qub.ac.uk/Study/international-students/international-scholarships.

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How to Apply

Apply using our online Queen's Portal and follow the step-by-step instructions on how to apply.

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Terms and Conditions

The terms and conditions that apply when you accept an offer of a place at the University on a taught programme of study.
Queen's University Belfast Terms and Conditions.

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