Data Science MSc/PgD/PgCert

The opportunity to exploit Big Data is recognised world-wide and some countries include it in their economic strategies. The UK Government identified Big Data as one of the 8 great technologies which will have a strong impact on growth and the Scottish Government highlights it as an emerging opportunity for Scotland.

Our MSc in Data Science aims to produce specialist data scientists with training in industry relevant data acquisition, storage, warehousing, analytics and visualisation tools and techniques and a good understanding of the needs of industry. The course will prepare graduates in technical disciplines for a career in the design and implementation use of computer-analytics and visualisation solutions for industry.

The course will focus on satisfying industry’s demand for data scientists who have the ability to:

• Apply appropriate data science tools and techniques to industry’s data in order to uncover important, previously unknown information only implicit in the data.
• Relate a company’s key performance indicators to a data science problem area in order to focus a data science task.
• Handle large amounts of real-time, non-persistent, data.
• Contribute to business decision-making by effectively communicating (potentially large volumes of) key data visually.
• Understand, clean up, summarise, interpret and manage data.
• Grasp key knowledge about new problem areas in order to communicate with end-users; understand key business needs and processes and identify added value through data analytics.
• Provide user-centred data analytics at an appropriate level.
• Protect and share data as appropriate.

The course will emphasise Big Data, covering not only traditional data management systems but also systems where data and/or its storage is unstructured.

Download a PDF of this course

MSc Data Science leaflet (PDF 216KB)

FULL-TIME

Year 1

Semester 1

• Data Warehousing
• Data Mining
• Advanced Data Management
• Intelligent Web Technologies

Semester 2

• Professional Skills for Data Scientists
• Big Data Analytics and Visualisation
• Data Science Development
• Advanced Data Science

Semester 3

• MSc Project

 PART-TIME

Year 1:

Semester 1

• Data Mining
• Data Management

Semester 2

• Professional Skills for Data Scientists
• Data Science Development

Year 2:

Semester 1

• Data Warehousing
• Intelligent Web Technologies

Semester 2

• Big Data Analytics and Visualisation
• Advanced Data Science

Year 3:

Semester 1

• MSc Project

Semester 2

• MSc Project

The University regularly reviews its courses. Course content and structure may change over time. See our Course Disclaimer for more information.

Throughout the course, content is complemented by practical work, allowing you to support your theoretical knowledge with practical experience in data storage, mining, warehousing, visualisation and analysis as well as transferrable skills. You will be taught through a mixture of lectures, tutorials, labs.  You will be invited to attend talks presented by highly-experienced researchers, speakers from industry, and members of the BCS (British Computer Society) on a wide range of industry-related topics. You will also be supported through our online virtual learning environment where you can access a wide variety of resources and other support materials.

The individual project provides an opportunity for applying specialist knowledge together with analytic, problem-solving, managerial and communication skills to a particular area of interest within data science. Working with the full support and guidance of an allocated project supervisor, you will be given the opportunity to propose, plan, specify, develop, evaluate, and present a substantial project.

Course Duration for Part-time Students

Part-time September start students

• A) Part-time September start students who would like to work on their project during the summer start their project in May of their second year and complete in December of their third year. (approximately 28 months)
• B) Part-time September start students who would like to avoid working on their project during the summer start their project in September of their third year and complete in May that year.  (approximately 33 months)

Part-time January start students

• C) Part-time January start students who would like to work on their project during the summer will start their project in January of their third year complete their project in August that year. (approximately 32 months)
• D) Part-time January start students who would like to avoid working on their project during the summer will start their project in January of their third year, have a break during the summer semester and continue their project September-December that year. (approximately 36 months)

• Applicants normally hold a 2:2 undergraduate honours degree or its equivalent in Mathematics, Statistics, Computing or any other analytical discipline.
• Applicants with a lower degree classification and / or relevant work experience will be considered on a case by case basis.

International students who do not meet our direct entry requirements for this course can gain additional entry points through our International College at Robert Gordon University.

English Language

Applicants whose first language is not English should have an IELTS of 6.0 overall, with no component lower than 5.5, or an equivalent.

We accept a variety of in-country and secure English language tests, find out more:

English Language requirements

* All entry requirements listed here should be used as a guide and represent the minimum required to be considered for entry. A small number of courses require higher levels, but this will be stated explicitly on your offer letter.

Students who perform particularly well during their first semester of studies will be invited to apply for any long placement opportunities (40-45 weeks) found by the Placement Office; alternatively, all students can seek their own long placement or a short placement.

However, permission to undertake a placement is at the discretion of the School.

Scholarships

Applicants to this course may be eligible for a scholarship. More information can be found on the Computing Scholarships pages.

The Data Lab - Funding Available

The Datalab MSc is a collaborative effort which started in 2015 between Robert Gordon University, The University of Dundee, The University of Stirling and The Data Lab, with the aim of developing the data science talent and skills required by industry in Scotland. Through this collaboration, each university has developed an MSc program based on its own strengths and capabilities, with the support of The Data Lab to facilitate industry involvement and collaboration, and provide funding and resources.

The Data Lab will fund 10 places at Robert Gordon University for the 2018/19 academic year.

To be eligible, applicants must have been resident in Scotland or the EU for at least three years and not for the purposes of study.

Find out more

Disclaimer

Course fees are reviewed periodically and so are subject to change for new applicants. All tuition fees are fixed for the duration of a course at the rate confirmed in your offer letter. You will also be liable to pay a graduation fee of £40 before receiving a University award.

Information for Postgraduate Applicants

Terms and Conditions of Admissions

The Terms and Conditions of Admission describe to applicants holding an offer of a place to study at RGU, the principal rights, duties and obligations of both the applicant and the University prior to enrolling on a course of study.

Terms and Conditions of Admissions (PDF 142KB)

The course prepares you for a career in Data Science. Job openings include: Data Scientist, Data Analyst, Data Visualisation Specialist, Data Manager, Database Designer/Manager, Data Mining Expert and Big Data Scientist.

Aberdeen is home to many multinational oil and gas companies and associated suppliers such as mainstream software houses, IT providers to major oil-related companies, specialist software consultancies, and venture capital start-ups.

The university is involved in a number of commercial collaborations on a local, national and international scale with organisations such as BP, British Geological Survey, Wood Group PSN, Accenture, WIPRO and many Aberdeen-based software development companies.

The course also prepares students for research careers by providing the skills necessary of an effective researcher. Suitable MSc graduates may continue to PhD programmes within the school. Further information can be found the School of Computing and Digital Media Postgraduate Research pages.

Dr. Eyad Elyan is a senior lecturer at the School of Computing Science and Digital Media, Robert Gordon University (RGU). He obtained his PhD in 3D Modeling, Representation and Recognition of Human Faces from the University of Bradford, United Kingdom. Eyad’s main research interests are focused on machine learning, content-based video retrieval,3D objects modeling and representation and machine vision. Current research activities are focused on data analytics, visualization and advanced machine learning, in particular ensemble learning.

He attracted funds to support his research in data analytics and machine vision from different resources including Innovate UK, the Data Lab Innovation Centre and Oil and Gas Innovation Centre (OGIC). Dr. Elyan is leading several projects with industrial partners across different domains including Construction, Sports Science, Oil and Gas and Health.

Dr. Elyan is a Fellow member of the British Higher Education Academy. He served as a Program Committee member for several international conferences and as a reviewer for several international journals in the area of machine vision, machine learning and data analytics. 

View Dr Eyad Elyan's staff profile