Embark on a career in a leading-edge field and master the exciting and challenging world of big data!
Big data techniques are revolutionising how organisations and industries acquire and analyse data, offering valuable insights into how people live, work, play, travel, shop and exercise. These insights are valuable to marketers, researchers, designers, city planners, app developers, educators and many more.
Studying an MSc in Big Data Technologies at GCU London will help you build the fundamental knowledge and practical skills for success in this fast-growing field. You'll develop competence in a range of emerging technologies: big data, cloud computing and the internet of things. You'll learn from the experts; GCU London is internationally recognised for the strength of its research in these exciting subjects, driving 21st century innovation.
With both full-time and part-time study available, the course is ideal for you if you have a background in computer science, software engineering, web technologies or computer engineering if you want to enhance or update your skills. If your background is in mathematics and electronics you'll also be well suited for this course.
The up-to-date curriculum keeps a career-focused approach, so you'll gain valuable skills you can immediately put to work in the industry.
- Apply leading-edge tools and technologies from companies such as IBM, Microsoft and SAS
- Explore industry-standard open-source development platforms such as Hadoop
- Achieve industry recognition with SAS joint certification in the programme's Data Analytics module
Your expertise in big data will enable you to provide new insights into human behaviour and psychology, which can help us build stronger and happier societies across the globe. Your work could shape smart, sustainable cities; remove barriers to education; help people make healthier choices day to day; improve public health and so much more. All meaningful ways of contributing to the Common Good.
When you graduate, you'll be a competitive candidate for roles as a systems developer, architect or administrator in data and analytics. You'll find opportunities in a diverse range of industries: engineering, pharmaceuticals, finance, healthcare, retail, security, smart environments and more.
Full-time students complete six taught modules; three in trimester A and three in trimester B and an MSc dissertation project in trimester C. Part-time students complete six taught modules; three in year one, three in year two and an MSc project in year three.
Big Data Landscape, Big Data Platforms, Cloud Computing and Web Services, Software Development for Data Science (Data Analytics), Dissertation, Internet of Things, IT Professional Issues and Project Methods.
Download the Programme Specification for a detailed breakdown of its structure, what you will learn and other useful information.
All entry requirements listed here should be used as a guide and represent the minimum required to be considered for entry. Applicants who are made a conditional offer of a place may be asked to achieve more than is stated.
UK honours degree 2:2 (or equivalent) in computing with software development, for example, computing, computer science, software engineering, web technologies and computer engineering. We also welcome applicants with Industry qualifications/experience within the GCU Recognition of Prior Learning (RPL) Policy.
English languageAcademic IELTS score of 6.0 (or equivalent) with no element below 5.5.
Please note: if you are from a majority English speaking country, you may not be required to provide further proof of your English Language proficiency.
Other academic and vocational qualifications
Each application to GCU is considered on an individual basis. If you do not have the typical academic entry qualifications, but can demonstrate relevant work experience and/or credits from recognised professional bodies, you may be eligible to enter this course via the University's Recognition of Prior Learning scheme.
The tuition fees you pay are mostly determined by your fee status. What is my student fee status?
Annual tuition fees 2021/22
Home (including Scotland): £8,700
International (including EU): £13,500
Fees are subject to change and published here for guidance only.
As a student at the University, there are additional fees and costs which may or may not apply to you, but that you should be aware of.
We provide high-quality education for a fair price; as the University for the Common Good, we are committed to offering accessible higher education for talented students by keeping our tuition fees low and providing a generous scholarship package of £2 million per year.
This course will equip you with the fundamental knowledge and skills of the core technologies for harnessing the big data challenges, including capture, curation, storage, integration, sharing, search, analysis, mining of large distributed unstructured datasets. Studies on this course are supported and enhanced uniquely by the University’s internationally excellent research strengths, especially in cloud computing, cyber security, Internet of Things and cyber-physical systems.
Of parallel importance in our course is to cultivate the professionalism which is expected within the industry. With all the future-proofing capabilities synthesised coherently together, graduates of the MSc in Big Data Technologies will be amongst the most highly-skilled ICT graduates, responding confidently to the needs and challenges in diverse big data application domains.
We have a range of scholarships at postgraduate level to support students financially.
You can read more about our focused activities and support at:
Athena Swan Bronze Award holder in recognition of its commitment to promoting gender equality among students and staff.
This degree has been accredited by BCS, The Chartered Institute for IT. Accreditation is a mark of assurance that the degree meets the standards set by BCS. An accredited degree entitles you to professional membership of BCS, which is an important part of the criteria for achieving Chartered IT Professional (CITP) status through the Institute. Some employers recruit preferentially from accredited degrees, and an accredited degree is likely to be recognised by other countries that are signatories to international accords.
Assessment is used to demonstrate achievement of learning outcomes. The methods of assessment include class tests, coursework assignments, practical tests and technical reports. Practical implementation and evaluation form a significant part of the assessment for the taught modules and for the work of the MSc dissertation.