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.
You may be required to sit an aptitude test. (Applicants with a minimum 2.2 Honours degree in a subject area not fulfilling the discipline criterion above require A Level Mathematics at grade B, or equivalent qualification acceptable to the University)
For EU and international students, a separate date will be arranged with the candidate and a test facility local to them.
Decisions will be issued within 10 working days from the date of the aptitude test.
In addition, a deposit of £400 will be required to secure a place.
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.
The Frontiers in Analytics module shows off some of the latest state-of-the-art techniques analytics in particular in Visual Analytics and Behavioural Analytics.
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.
"The MSc Data Analytics will equip successful candidates for any data scientist role and make them highly marketable for what is now seen as “the sexiest job in the 21st century” as reported by The Harvard Business Review."
Professor Adele MarshallProgramme Director
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.
Data Analytics Fundamentals
Databases and Programming Fundamentals
Frontiers in Data Analytics
Analytics in Action
Individual Industry Based Project
Indicative number of modules per semester: 3
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 of 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.
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 9 am-5 pm.
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 week the schedule will consist of 9 am-5 pm with approximately equal numbers of lectures (in the mornings) and labs (in the afternoons).
Assessments associated with the course are outlined below:
Normally a 2.2 Honours first 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 subject area not fulfilling the discipline criterion above require A Level Mathematics at grade B, or equivalent qualification acceptable to the University, and will be required to pass an aptitude test.
For information on international qualification equivalents, please check the specific information for your country.
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 the 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.
As a result of the COVID-19 pandemic, we will be offering Academic English and Pre-sessional courses online only from June to September 2020.
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.
Northern Ireland (NI)
England, Scotland or Wales (GB)
Other (non-UK) EU
All tuition fees quoted are for the academic year 2020-21. Tuition fees will be subject to an annual inflationary increase unless explicitly stated otherwise.
Terms and Conditions for Postgraduate applications
Due to high demand, there is a deadline for applications.
You will be required to pay a deposit of £400 pounds to secure your place on the course.
This condition of the offer is in addition to any academic or English language requirements.
Additional course costs
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.
Data Analytics costs
There are no specific additional course costs associated with this programme.
How do I fund my study?
The Department for the Economy will provide a tuition fee loan of up to £5,500 per NI / EU student for postgraduate study.
A postgraduate loans system in the UK offers government-backed student loans of up to £10,609 for taught and research Masters courses in all subject areas. Criteria, eligibility, repayment and application information are available on the UK government website.