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.
GCU's MSc in Big Data Technologies helps students 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 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 programme is ideal for someone with a background in computer science, software engineering, web technologies or computer engineering who wants to enhance or update their skills. Those with backgrounds in mathematics and electronics are also well suited.
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.
Graduate prospects
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.
International student start dates
For new international students, orientation events start on 14 September 2018 . This extra time is specifically designed to assist new international students in settling in the UK and GCU prior to the start of general student induction and teaching.
There will be a whole host of fun and informative activities taking place during this period, including campus and city tours, as well as welcome events where you can meet other international students.
More information is available from our award-winning Visa Immigration Support & Advice (VISA) team.
Why choose this programme?
This programme will equip students 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 programme are supported and enhanced uniquely by the University’s internationally excellent research strengths, especially in cloud computing, cybersecurity, Internet of Things and cyber-physical systems.
Of parallel importance in our programme 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.
Work placements
Students will be made aware of placement opportunities provided by our industry partners. Typically a placement would be undertaken after graduating from the MSc programme but opportunities can sometimes be made available for students to undertake their MSc Dissertation in partnership with a commercial company.
Assessment methods
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.