Taught course

Big Data

Institution
University of Stirling · Faculty of Natural Sciences
Qualifications
MScPGDipPGCert

Entry requirements

Applicants normally require a first or second class Honours degree in a numerate subject such as maths, computing, engineering or an analytic science, from a British university, or an equivalent qualification from an institution recognised by the University. Applicants without these formal qualifications but with significant appropriate work experience are encouraged to apply.

Months of entry

September

Course content

This is an exciting new programme starting its second year in September 2015.

Big Data skills are in high demand and they attract high salaries. The MSc Big Data at the University of Stirling is a taught advanced Masters degree covering the technology of Big Data and the science of data analytics.

Industry and Employer Partnerships

The Stirling MSc in Big Data has been developed in partnership with global and local companies who employ data scientists. HSBC have a development centre in Stirling and have provided some very interesting Big Data projects to our students. Amazon’s development centre in Scotland is close by in Edinburgh, and they often recruit data scientists. The course features a long summer project, generally in partnership with a company or technology provider, that provides students with a showcase of their skills to take to employers or launch online.

Computing Science and Mathematics has strong links with industry and is host to world-class research in the areas of Computational Heuristics, Operational Research, Decision-Support, Cognitive Computation, and the Modelling and Analysis of Complex Systems. We regularly invite industry experts to share their expertise through seminars and talks.

The course covers Big Data technology, advanced analytics and industrial and scientific applications. The syllabus includes:

  • Mathematics for Big Data
  • Big Data theory and computing foundations
  • Big databases and NoSQL
  • Analytics, machine learning and data visualisation
  • Optimisation and heuristics for big problems
  • Distributed and parallel systems
  • Scientific and commercial applications
  • Student projects

Course objectives and content

  • An understanding of the issues of scalability of databases, data analysis, search and optimisation
  • The ability to choose the right solution for a commercial task involving big data, including databases, architectures and cloud services
  • An understanding of the analysis of big data including methods to visualise and automatically learn from vast quantities of data
  • An appreciation of the size of search spaces in large problems and the ability to choose an appropriate heuristic to find a near optimal solution
  • The programming skills to build simple solutions using big data technologies such as MapReduce and scripting for NoSQL, and the ability to write parallel algorithms for multi processor execution.

The Big Data MSc is a mix of practical technology such as Hadoop, NoSQL, and Map-Reduce, important maths and computing theory, and advanced computational techniques. The course will teach you what you need to know to collect, manage and analyse big, fast moving data for science or commerce.

The course comprises two 15-week semesters of taught modules, and the MSc dissertation project over three months at the end.

This is a practical course and the assessment reflects that. Each module has an assignment and an exam, but the emphasis is on the course work.

Technology

Here are some of the technologies you will learn about on our Big Data MSc:

You may graduate with the Postgraduate Diploma after two semesters, or you may continue with a three-month project and dissertation to qualify for the award of the MSc degree.

Career opportunities

Demand for people with big data skills is projected to grow rapidly in the coming years. Average salaries are higher in Big Data jobs than the IT average and the skills shortage will make that gap bigger.

The Stirling Big Data MSc is run in partnership with industry and is designed to produce graduates with the skills that companies need

Stirling computing graduates have a good track record in finding well-paid jobs. Previous students have been very successful in obtaining suitable employment in a considerable diversity of posts – with small companies, with major international organisations including Accenture, IBM, HP, Microsoft, Reuters and major financial institutions such as HBOS, as well as with Local Authority and Government bodies. A number of graduates have continued their studies towards a PhD.

In the Guardian University Guide 2013, Computing Science at Stirling ranks 12th overall in UK and 1st for student satisfaction with course and feedback.

Fees and funding

UK students
£4500
International students
£13500

For information on possible sources of funding, visit: http://www.stir.ac.uk/postgraduate/financial-information/sources-of-funding/

Qualification and course duration

MSc

full time
12 months

PGDip

full time
9 months

PGCert

full time
3 months

Assessment

AssessmentWhat kind of work will I be doing? (proportionally)
Written/ formal examinations40
Written coursework / continuous assessment30
Dissertation30 (15000 words)

Course contact details

Name
Mr Kevin Swingler
Email
kms@cs.stir.ac.uk
Phone
+ 44 (0) 1786 467436