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Course summary

Big data is increasingly important in today’s commercial landscape. As a data scientist specialising in big data, you’ll help companies make sense of large amounts of structured and unstructured data, providing rapid insights that enable them to make better, quicker decisions. The MSc Big Data is a taught advanced Masters degree covering the technology of Big Data and the science of data analytics. You’ll gain practical skills in big data technology, advanced analytics and industrial and scientific applications. The course will teach you how to collect, manage and analyse big, fast moving data for science or commerce. You’ll learn skills in cutting-edge technology such as Data Analytics, R, Hadoop, NoSQL and Machine Learning. At the same time, you’ll delve into important maths and computing theory, and learn the advanced computational techniques you need to develop your career in data science. Our MSc has been developed in partnership with global and local companies who employ data scientists. Since the course was launched in 2012 we have developed a great relationship with employers who are looking for the skills that we teach. The University of Stirling is associated with The Data Lab, an Innovation Centre that aims to develop the data science talent and skills required by industry in Scotland. It also supports our students with funding, networking and routes into employment. We also have close links with the Scottish Informatics and Computing Science Alliance (SICSA). As a graduate in Big Data you’ll be able to work in a wide range of sectors such as digital technologies, energy and utilities, financial services, public sector and healthcare. Scotland is a growing and dynamic country with an exciting future at the heart of the data science revolution. £661 million invested in vision of turning capital city into the ‘Data Capital of Europe’ (Source: Scottish Development International).


The course covers Big data technology, advanced analytics and industrial and scientific applications. The syllabus includes: mathematics for big data; python scripting; big data theory and computing foundations; big databases and NoSQL; analytics, machine learning and data visualisation; optimisation and heuristics for big problems; hadoop and mapreduce; scientific and commercial applications; student projects.

Assessment method

Each module has an assignment and an exam, but the emphasis is on the course work.

Entry requirements

A minimum of a 2nd Class Honours degree or equivalent in a numerate subject such as maths, computing, engineering or an analytic science. Applicants without these formal qualifications but with significant appropriate work experience are encouraged to apply.

Fees and funding

Tuition fees

No fee information has been provided for this course

Additional fee information

for further information on course costs, please refer to the University website;

Sponsorship information

For information on funding and scholarships, please see here:

Big Data at University of Stirling - UCAS