30Apr
PostgraduateCourse summary
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. Utilise industry-standard leading-edge tools and technologies, including the latest AI and ML techniques. Apply a wide range of industry-standard open-source development platforms and databases. Confidently analyse and visualise data sources, to deliver new levels of understanding. 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 data scientist, data analyst, systems developer or systems architect. You'll find opportunities in a diverse range of industries: engineering, pharmaceuticals, finance, healthcare, retail, security, smart environments and more. Scottish applicants to MSc Big Data Technologies have the opportunity to receive a fully-funded scholarship to study in September 2022 from the Data Lab, in partnership with the Scottish Funding Council (subject to confirmation). Find out more here.
Modules
Full-time students complete eight taught modules; four in trimester A and four in trimester B and undertake an MSc dissertation project in the trimester following the completion of taught modules. Part-time students complete eight taught modules; four in year one, four in year two and undertake an MSc dissertation project over two trimesters following the completion of taught modules. Module list: Big Data Landscape, Software Development for Data Science, Artificial Intelligence and Machine Learning, Data Ethics and Research Methods. Cloud Computing and Web Services, Internet of Things, Big Data Platforms, Data Visualisation. Dissertation
Assessment method
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.
Professional bodies
Professionally accredited courses provide industry-wide recognition of the quality of your qualification.
- BCS - The Chartered Institute for IT
Entry requirements
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 Language requirements: Academic 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.
English language requirements
| Test | Grade | Additional details |
|---|---|---|
| IELTS (Academic) | 6 | Overall score of 6.0 with the minimum of 5.5 in each element |
Fees and funding
Tuition fees
No fee information has been provided for this course
Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .
Additional fee information
No additional fees or cost information has been supplied for this course, please contact the provider directly.
Provider information
Glasgow Caledonian University
City Campus
Cowcaddens Road
Glasgow
G4 0BA