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.
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 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
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 B.Sc. Honours degree in a subject area not fulfilling the discipline criterion above require Mathematics A-level at grade B, or equivalent qualification acceptable to the University, and will be required to pass an aptitude test.
Dates of aptitude tests to be confirmed in due course.
For information on international qualification equivalents please select Your Country from the list on our International Students website.
Applicants for whom English is not their first language must satisfy University requirements for English language, by providing evidence of an IELTS* score of 6.0, 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.
For more information on English Language requirements for EEA and non-EEA nationals see http://go.qub.ac.uk/EnglishLanguageReqs
INTO at Queen's can provide tuition to help you meet the University's English Language Requirements, please see http://www.intohigher.com/qub
Please note: Applications for this course, received after 30th June may not be accepted. A deposit will be required to secure a place.
Applications for postgraduate study may be made online here.
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For more information please read our Equality and Diversity Policy.
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