Find a Degree Postgraduate Taught Programmes Data Analysis, Visualisation and Communication

Programme Details

Data, and the information locked inside, is now recognised as the definitive source for competitive advantage in every economic sector, and a crucial contributor to health and wellbeing. The true value however, can only be unlocked if the data is understood and communicated optimally.

The programme is based on a strong collaboration between Human Geography and Computing Science, with input where possible from experts throughout the university (e.g. in Physics, Seismology, Environmental Science, and Healthcare). It also benefits from the strong partnerships we have with public sector (e.g. SNH, SEPA, RSPB, NHS) and industry (e.g. IBM, Philips Electronics, Nuance, Arria, First).

The programme is appropriate for students from a wide variety of backgrounds who are interested in developing specific skills to make them more competitive in the job market, or as they apply for additional higher degrees.

While some students may have a background in computing science, applied mathematics/physics, or engineering, the programme will also appeal to students from disciplines where relevant skills in data analysis (or cognitive science) are taught, such as Human Geography and Sociology.  This programme will be a way of preparing you to use and extend your existing skills for the benefit of the Digital Economy. 

Aims

Major global organisations such as Tesco, Amazon, BP and the BBC, to name a few, work extremely hard to unlock key information from within data to help improve business efficiencies and customer engagement, increase sales and better understand consumer buying behaviours.

At the same time, local, regional, and national public agencies work with the collection and communication of data to ensure that they are both providing efficient services to their customers and citizens and keeping them informed of things that may improve their quality of life. Accessing the right information and communicating it effectively really does provide endless opportunities for success.

There is significant evidence showing a shortfall in people with the appropriate skills necessary to fully engage in the data chain, which is providing concern to some major employers. This MSc programme will go some way to addressing this shortfall in skills and will put you in a strong position for careers in this vitally important business process.

Syllabus

Core modules:

Data Management

The course is designed to provide fundamental understanding of data management techniques in order to ensure that you are aware of the processes and procedures necessary for good data practice. The course will provide instruction covering a full data management process, including instruction on the development of data management plans, organisation of data and databases, documentation, development of metadata, issues related to data storage and security, data protection, and data sharing. Both technical and regulatory issues of concerns will be addressed (including ethical considerations).

Data Analysis and Visualisation

This course is intended to introduce you to methods of data analysis and visualisation. Primary focus will be on ensuring that you are aware of and able to apply appropriate methods depending upon the type of data being analysed, the questions to which answers are being sought, and the audience to which visualisations are being targeted.

Linked Data and the Semantic Web 

An abundance of textual information is available on the Internet. As it is dispersed over web pages, it is difficult to extract the information and understand its overall meaning. In this course, students will learn information extraction and text mining theory and techniques, corpus construction, and programming tools (e.g. NLTK and GATE) in order to extract and structure information from text. The emphasis is hands-on and realistic. Using the techniques and tools, students will be able to start to unlock the economic, cultural, and social value of web-based textual information, gaining valuable skills in an expanding market. 

Research Methods 

Introducing you to additional relevant research methods for data analysis in a practical context that builds upon methods covered in data analysis and visualisation. The course provides substantive support for development of your individual project. Topics studied in detail include strategy formulation for effective literature review, various methodological approaches, the selection of appropriate methods for carrying out specified research exercises and the production of feasible research proposals and programmes of work.

Electives

Based on your interests, you can select from a range of relevant electives already offered within the University. For example:

Natural Language Generation

Human Computer Interaction 

Transport Geography 

GIS Tools and Techniques I

GIS Tools and Techniques II

Aspects of Digital Mapping & Visualization

Current applications of GIS

Marketing Management

Database Systems and Big Data

Information Extraction and Text Analytics

Group Projects (30 Credits):
• One group project in each teaching semester

Summer Semester:
• Individual Project 

Assessment

Courses are assessed by continuous assessment, by written examination or by a combination of these, as prescribed by each course co-ordinator. 

Teaching

The MSc will be taught by experts in data analysis, management, visualisation and communication from the departments of Natural and Computing Sciences and Geography & Environment, along with other disciplines for elective topics. External partners will be drawn in for guest lectures and evaluation in order to provide practical assessment of skills development. 

Careers

There is a substantial shortage of people with relevant skills, across a number of industries. Evidence available shows that companies are looking for people with the ability to analyse interpret and communicate data.

- Deloitte reported recently that “there is increasing demand for individuals with a portfolio of skills able to manipulate quantitative data, present it in innovative ways and generate commercial and policy insights from it”

- Shakespeare recommends that “Government should task the research councils to be strategic in their funding of graduate training to encourage the growth of basic data science and inter-disciplinary projects, and consider further increasing funding available for teaching of data disciplines.”

- Computer Weekly, 2013 reported that “Government calls for more data scientists in the UK” - http://www.computerweekly.com/news/2240208220/Government-calls-for-more-data-scientists-in-the-UK

- Forbes in 2013 looked at “Combating the Big Data skills shortage” - http://www.forbes.com/sites/bwoo/2013/01/18/combating-the-big-data-skills-shortage/

Data has become a core component of business activity in a range of sectors, including both public and private non-profit and for-profit enterprises. Some related job areas include data science, data analysis, data visualisation, and data communications analyst.

Academic Requirements 

Our minimum entry requirement for this programmes is a Computing Science degree at 2:2 (lower second class) UK Honours Degree (or an Honours degree from a non-UK Institution which is judged by the University to be of equivalent worth).

Students with a degree in the area of Biology, Economics, Geography, Politics, Psychology or Sociology at 2:1 (upper second class) will also be considered. Those with a 2:2 may still apply as the application will be reviewed by the selector for suitability. 

Key subjects you must have covered: mathematics and statistics.

Document Requirements 

For this application we require at least:

  • A full transcript showing all the subjects you studied and the marks you have achieved in your degree(s) so far (original and official English translation)
  • Detailed personal statement of no more than 500 words 
  • Current CV/Resume
  • Academic reference (or employer reference if 2+ years' experience)

English Language 

Even if you have been educated in the medium of English you must meet our English Language requirements. These are located atwww.abdn.ac.uk/study/international/english-requirements.php. This programme requires that you meet the 'Postgraduate Standard' level of English proficiency. If you are in doubt about your proficiency in English, contact the British Council office or its equivalent in your country. If your first language is not English, it is important that your proficiency in English is good in order for you to study successfully at the University of Aberdeen . Without this ability you will find great difficulty in understanding lectures, producing written work and sitting examinations. 

Intakes

We have one intake of students each year - September.

Late applications may be asked to wait until the next intake should the programme coordinator feel there is insufficient time to consider the application. Prospective students who require a visa to study in the UK are advised to apply as early in the year as possible to secure a place.

Applications received after 30th June from students who need to apply for a visa to study in the UK will not be processed for entry but will be considered for entry into the following intake as appropriate.

Fees

2016/17 Fees

Home/EU - £4,500

International - £13,800

Funding

Funding opportunities can be found in our searchable Funding Database. You are advised to search the database as a broad range of funding exists much of which you may be eligible for.

A list of funding opportunties is also maintained on the College of Physical Sciences Funding Page.

University of Aberdeen Alumni Discount Scheme

The University of Aberdeen is very pleased to offer a 20% discount on postgraduate tuition fees for all alumni who have graduated (or about to graduate) with a degree from the University of Aberdeen. More Information

Contact

Related Information

General Information

Student Recruitment & Admissions Service
University of Aberdeen
The Hub
King's College
ABERDEEN AB24 3TU

Tel: +44 (0)1224 272090 / +44 (0)1224 272091
Fax: +44 (0)1224 272576
Email: sras@abdn.ac.uk