Data-Intensive Analysis (MSc) 2018 entry

The MSc in Data-Intensive Analysis is an interdisciplinary course providing students with an understanding of how data is used to gain useful insights in all areas of scientific endeavour. The programme has a substantive statistical component – both theory and practice – allied to computational data science and visualisation.

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Course type

Postgraduate; leading to a Master of Science (MSc)

Course dates

  • Start date: 10 September 2018
  • End date: 30 September 2019

If you started this programme in 2017, you can find information about 2017 entry on the 2017 Data-Intensive Analysis page. Information about all programmes from previous years of entry can be found in the archive.

Course duration

One year full time or two years part time

Entry requirements

A good 2.1 Honours undergraduate degree, plus evidence of some previous programming experience.

If you studied your first degree outside the UK, see the international entry requirements.

English language proficiency. See English language tests and qualifications.

The qualifications listed are indicative minimum requirements for entry. Some academic Schools will ask applicants to achieve significantly higher marks than the minimum. Obtaining the listed entry requirements will not guarantee you a place, as the University considers all aspects of every application including, where applicable, the writing sample, personal statement, and supporting documents.

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Tuition fees

UK and EU: £8,500
Overseas: £20,980

Application deadline

While there is no firm deadline for MSc applications, we strongly recommend that you submit your completed application as early as possible, particularly if you are also applying for funding or a visa. To maintain staff-student ratios, the School reserves the right to stop accepting applications once the programme is full.

Application requirements

  • CV
  • personal statement (optional)
  • two original signed academic references
  • academic transcripts and degree certificates 
  • evidence of English language proficiency (required if English is not your first language).

For more guidance, see supporting documents and references for postgraduate taught programmes.

Course information

The MSc in Data-Intensive Analysis is a one-year taught programme run collaboratively by the Schools of Computer Science and Mathematics and Statistics. The course consists of two semesters of taught modules followed by an 11-week project leading to the submission of a 15,000-word dissertation in August.

Highlights

  • The course develops practical skills in derivation, validation and deployment of predictive models based on collected data, and provides training in the use of industry- and research-standard technologies and techniques.
  • Students undertake a significant project including a wide-ranging investigation leading to their dissertation, which enables them to consolidate and extend their specialist knowledge and critical thinking.
  • Students have 24-hour access to modern computing laboratories, provisioned with dual-screen PC workstations and group-working facilities.

Teaching format

The taught part of this MSc programme includes five compulsory modules in statistics and data analysis, plus a choice of two from four modules in Computer Science. Teaching methods include lectures, seminars, tutorials and practical classes. Most modules are assessed through practical coursework exercises and examinations. Class sizes typically range from 10 to 50 students.

All students are assigned an advisor who meets with them at the start of the year to discuss module choices and is available to assist with any academic difficulties during the year. A designated member of staff provides close supervision for the MSc project and dissertation.

Further particulars regarding curriculum development.

Modules

The modules in this programme have varying methods of delivery and assessment. For more details about each module, including weekly contact hours, teaching methods and assessment, please see the latest module catalogue, which is for the 2017–2018 academic year; some elements may be subject to change for 2018 entry.

Students take five compulsory modules. 

  • Advanced Data Analysis: covers modern modelling methods for situations where the data fails to meet the assumptions of common statistical models and simple remedies do not suffice.
  • Computing in Statistics: introduces and provides experience with the software package SAS and the statistical language and environment R. 
  • Data Analysis: provides coverage of essential statistical concepts, data manipulation and analysis methods, and software skills in commercial analysis packages.
  • Knowledge Discovery & Datamining: covers many of the methods found under the banner of "Datamining", building from a theoretical perspective but ultimately teaching practical application.
  • Statistical Modelling: covers the main aspects of linear models and generalized linear models, including model specification, various options for model selection, model assessment and tools for diagnosing model faults.

Students choose two of the following optional modules. 

  • Data-Intensive Systems
  • Information Visualisation: explores how to utilise visual representations to make information accessible for exploration and analysis.
  • Masters Programming Projects: reinforces key programming skills gained during the first programming module of the programme and offers increasing depth and scope for creativity.
  • Object-Orientated Modelling, Design and Programming
  • Programming Principles and Practice: introduces computational thinking and problem solving skills to students who have no or little previous programming experience.

During the second semester, students work with staff to define and agree upon a topic for the extended project, which they will work on during the final three months of the course, and which culminates in a 15,000-word dissertation. Dissertation projects may be group-based or completed individually (students are assessed individually in either case).

The dissertation typically comprises: a review of related work; the extension of existing or the development of new ideas; software implementation and testing; analysis and evaluation. Students are required to give a presentation of their work in addition to the written dissertation.

Each project is supervised by one or two members of staff, typically through regular meetings and reviews of software and dissertation drafts.

If students choose not to complete the dissertation requirement for the MSc, there is an exit award available that allows suitably qualified candidates to receive a Postgraduate Diploma instead, finishing the course at the end of the second semester of study.


The modules listed here are indicative, and there is no guarantee they will run for 2018 entry. Take a look at the most up-to-date modules in the module catalogue.

 

Visit St Andrews

If you are interested in studying at St Andrews, join us at an open day to explore the town, find out about our courses and meet current students.

Postgraduates

Upcoming visiting days:

  • Wednesday 14 November 2018

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Conferences and events

The School of Computer Science organises a regular programme of colloquia, talks and seminars by external and internal speakers from both industry and academia. The talks are aimed at bringing the diversity, excitement and impact of computer science from around the globe to staff and students within the School.

The St Andrews Computing Society (STACS) regularly organises hackathons and other events open to local and external participants, including MSc students. These are very popular events, often supported by industrial sponsors.

The Computer Science blog regularly publishes news and events. 

Funding

There are many potential scholarships and support schemes available to postgraduates.

Recent Graduate Discount
The University of St Andrews offers a 10% discount in postgraduate tuition fees to students who are eligible to graduate or who have graduated from St Andrews within the last three academic years and are starting a postgraduate programme with the University of St Andrews.

Find out more about postgraduate scholarships. 

After the MSc

Research degrees

In addition to the MSc, the School offers a two-year Master of Philosophy (MPhil) degree option in Data-Intensive Analysis.

The EngD programme in Computer Science is a 4-year Engineering Doctorate involving an industrial partner and incorporating a 30-week taught component and a 170-week individual research component. Students who have already completed an MSc may be able to proceed directly to the individual research component of the EngD.

Many of our graduates continue their education by enrolling in PhD programmes at St Andrews. The School of Computer Science is highly rated for its theoretical and practical research in areas such as AI, symbolic computation, networking, computer communication systems, human computer interaction, and systems engineering, and offers research opportunities leading to a PhD in Computer Science.

Engineering and Physical Sciences Research Council
The EPSRC offers a variety of research studentship funding in Computer Science.

PhD in Computer Science

Careers

Alumni of Computer Science MSc programmes have gone on to work in a variety of global, commercial, financial and research institutions, including:

  • Amadeus
  • Amazon
  • Atlas
  • Avaloq
  • Barclays Capital
  • BP
  • BT Openreach
  • Capricorn Ventis
  • FactSet
  • Hailo
  • Hewlett Packard
  • Hitachi Data Systems
  • Microsoft
  • OpenBet
  • Rockstar
  • Royal Bank of Scotland
  • Sky
  • Skyscanner
  • Symantec
  • TriSystems

The Careers Centre offers one-to-one advice to all students on a taught postgraduate course and offers a programme of events to assist students to build their employability skills.

Contact information

School of Mathematics and Statistics
University of St Andrews
Mathematical Institute
North Haugh
St Andrews
KY16 9AL

Phone: +44 (0)1334 46 2344 
Email: maths-pgstats@st-andrews.ac.uk

Mathematics and Statistics website

Policies

Admission to the University of St Andrews is governed by our Admissions policy.

Curriculum development

As a research intensive institution, the University ensures that its teaching references the research interests of its staff, which may change from time to time. As a result, programmes are regularly reviewed with the aim of enhancing students' learning experience. Our approach to course revision is described online. (PDF, 72 KB).

Tuition fees

The University will clarify compulsory fees and charges it requires any student to pay at the time of offer. The offer will also clarify conditions for any variation of fees. The University’s approach to fee setting is described online. (PDF, 84 KB).