Data-Intensive Analysis MSc

Program Overview

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Data-Intensive Analysis (MSc) 2025 entry

Harness the power of big data for scientific insight, and open up new career opportunities in industry and research.

Application Deadline

Thursday 7 August 2025

Starts

September 2025

Duration

One year full time

School

School of Computer Science

Fees

• UK: £12,030
• Rest of the world: £29,990

Why Study This Course?

This is an interdisciplinary course from the School of Mathematics and Statistics and the School of Computer Science. It provides an understanding of how data is used to gain useful insights in all areas of science. The programme has a substantive statistical component – both theory and practice – allied to computational data science and visualisation.

• Develop your practical skills in derivation, validation and deployment of predictive models based on collected data, and train in the use of industry- and research-standard technologies and techniques.
• Extend your specialist knowledge and critical thinking with a project involving a wide-ranging investigation and a substantial software development, leading to your dissertation.
• Access modern computing laboratories 24 hours a day. These labs are student spaces which support the close-knit community within the School where students at different stages of study and disciplinary interests can meet. There are also areas where groups can work together on projects.

Teaching

A mix of lectures, seminars, tutorials and practical classes.

Class Sizes

Typically from 15 to 50 students.

Dissertation

A three-month project leading to a 15,000-word dissertation.

Assessment

Practical coursework exercises and exams.

Modules

The St Andrews degree structure is designed to be flexible. You study compulsory modules delivering core learning together with optional modules you choose from the list available that year.

You will choose four optional modules.

If you 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 (PGDip) instead, finishing the course at the end of the second semester of study.

Compulsory

• Introductory Data Analysis: covers essential statistical concepts and analysis methods relevant for commercial analysis.
• 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.
• Knowledge Discovery and Datamining: covers many of the methods found under the banner of datamining, building from a theoretical perspective but ultimately teaching practical application.
• Applied Statistical Modelling using GLMs: covers the main aspects of linear models and generalised linear models, including model specification, various options for model selection, model assessment and tools for diagnosing model faults.

Optional

• Computing in Statistics: teaches computer programming skills, including principles of good programming practice, with an emphasis on statistical computing.
• Data-Intensive Systems: presents the programming paradigms, algorithmic techniques and design principles for large-scale distributed systems, such as those utilised by companies such as Google, Amazon and Facebook.
• 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: introduces and reinforces object-orientated modelling, design and implementation to provide a common basis of skills, allowing students to complete programming assignments within other MSc modules. The module assumes a substantial amount of prior programming experience equivalent to having completed an undergraduate degree in Computer Science.
• Programming Principles and Practice: introduces computational thinking and problem-solving skills to students who have no or little previous programming experience.
• Software for Data Analysis: covers the practical computing aspects of statistical data analysis focusing on widely used packages, including data-wrangling and visualisation.

Project

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, however, 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 may be 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. Supervisors and topics may be from either of the schools of Computer Science or Mathematics and Statistics and many are in collaboration with companies or other external bodies.

What It Will Lead To

Careers

In an era of big data, graduates from the School of Computer Science are in high demand, and there are a wide range of meaningful, exciting, and well-paid career opportunities open to you.

We are committed to supporting your career aspirations, whatever stage your career is at. We offer:

• Access to our extensive global alumni community for advice and mentoring
• One-to-one guidance covering everything from career choice to application support and interview coaching
• Employer connections, global vacancies, and practical experiences
• Academic and professional skills development

Elevate Your Career

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

• ASOS
• Civil Service
• Google
• Lloyds Banking Group

Further Your Education

Data-Intensive Analysis graduates can pursue PhDs at St Andrews or beyond.

The School of Computer Science also offers a two-year Master of Philosophy (MPhil) degree option in Data-Intensive Analysis, and the 4-year EngD programme in Computer Science.

Accreditation

Graduates of the MSc programme can apply to the Royal Statistical Society for the professional status of Graduate Statistician (GradStat) without the need for further examination.

Why 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.

The School 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) and Women in Computer Science at St Andrews (WICS) regularly organise hackathons and other events open to local and external participants, including Masters students. These are very popular events, often supported by industrial sponsors.

The School of Mathematics and Statistics

has active research groups in:

• Applied Mathematics
• Pure Mathematics
• Mathematical Biology
• Statistics

Events

There are a number of different seminars held each week in the School of Mathematics and Statistics. These include:

Pure Mathematics

• Pure Mathematics colloquia
• Analysis Group Seminars

Statistics

• Statistics seminars
• Centre for Research into Ecological and Environmental Modelling seminars

Alumni

When you graduate you become a member of the University's worldwide alumni community. Benefit from access to alumni clubs, the Saint Connect networking and mentoring platform, and careers support.

“At St Andrews you are in a friendly and team-working environment where you feel that you are a student with many exceptional mentors. It has been amazing to learn about the statistical world in an applied way on real-life examples and scenarios rather than just the theory.”

Andreas - Paphos, Cyprus

Entry Requirements

• A 2:1 undergraduate Honours degree in a STEM subject or equivalent professional experience. If you studied your first degree outside the UK, see the international entry requirements.
• Demonstrable interest or experience in statistical data analysis in an academic or professional setting.
• Some experience with object-oriented programming such as R, Python, C++ or Java.
• 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.

Application Requirements

• a one-page personal statement directly addressing entry requirements and including relevance of previous degree or experience, your interests in statistical analysis, and your object-oriented programming experience
• a CV with a history of your education and employment to date
• academic transcripts and degree certificates
• two original signed academic or professional references, ideally one academic reference and a professional reference if experience is to be considered

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

English Language Proficiency

If English is not your first language, you may need to provide an English language test score to evidence your English language ability. See approved English language tests and scores for this course.

Fees and Funding

• UK: £12,030
• Rest of the world: £29,990

Before we can begin processing your application, a payment of an application fee of £50 is required. In some instances, you may be eligible for an application fee waiver. Details of this, along with information on our tuition fees, can be found on the postgraduate fees and funding page.

Scholarships and Funding

We are committed to supporting you through your studies, regardless of your financial circumstances. You may be eligible for scholarships, discounts or other support:

• GREAT Scholarship
• St Andrews Sanctuary Scholarship
• St Leonard's funding opportunities
• Graduate discount (15% off tuition fees)

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