Overview
The MSc in Data-Intensive Analysis at the University of St Andrews 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.
Key facts
- 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.
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. They are committed to supporting your career aspirations, whatever stage your career is at. They offer:- Access to 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
Programme Structure
Courses include:
- Advanced Data Analysis
- Knowledge Discovery and Datamining
- Applied Statistical Modelling using GLMs
- Computing in Statistics
- Data-Intensive Systems
- Information Visualisation
Key information
Duration
- Full-time
- 12 months
Start dates & application deadlines
- Starting
- Apply before , International
- Apply before , National
-
Language
IELTS & PTE Test Preparation
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- Live classes with current and ex-examiners
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Credits
Delivered
Campus Location
- St Andrews, United Kingdom
Disciplines
Data Analytics View 248 other Masters in Data Analytics in United KingdomWhat students do after studying
Academic requirements
English requirements
IELTS & PTE Test Preparation
Admission to your dream university starts with a high IELTS or PTE score. Earn your target score with E2's guided test preparation.
- Study on your own schedule
- Live classes with current and ex-examiners
- Accurate score assesment, always
- E2 Score Guarantee - Get your score or your money back!
Other requirements
General 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.
- 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
Tuition Fees
-
International Applies to you
Applies to youNon-residents31450 GBP / year≈ 31450 GBP / year -
Domestic Applies to you
Applies to youCitizens or residents12630 GBP / year≈ 12630 GBP / year
Living costs
Saint Andrews
The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.
Funding
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Scholarships Information
Below you will find Master's scholarship opportunities for Data-Intensive Analysis.
Available Scholarships
You are eligible to apply for these scholarships but a selection process will still be applied by the provider.
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