Overview
The Financial Data Science programme offered at University of Surrey is taught by expert staff and supported by industrial advisers from financial City institutions, and studying in Guildford – within easy reach of London’s financial hub – the course will greatly enhance your employability in financial and related areas.
Career opportunities
- You’ll learn how to implement cutting-edge data science methods and develop a solid understanding of the mathematical foundations of machine learning tools. You’ll also dive into the dynamics of financial markets – exploring asset pricing, risk management and portfolio theory. You will master advanced modelling techniques and quantitative methods to analyse real-world financial data, and you’ll discover the transformative power of AI and machine learning in deciphering market behaviours and making data-driven predictions. Through practical hands-on exercises and projects, you’ll gain the skills to apply these techniques effectively, enabling you to excel in this evolving and exciting field. Both data science and mathematics are of paramount importance to all aspects of science, technology and – particularly – modern finance. The logical insights, analytical skills and intellectual discipline gained from this course are highly sought after in each of these areas, as well as in a broad range of other disciplines such as law, business, management, e-commerce and the creative arts. The University of Surrey has an excellent record for graduate employability. 94 per cent of our mathematics postgraduate students go on to employment or further study (Graduate Outcomes 2024, HESA).
Get more details
Visit programme websiteProgramme Structure
Courses include:
- Artificial Intelligence And Financial Informatics
- Financial Markets And Derivative Pricing
- Derivatives Markets
- Principles Of Data Science
- Mathematics Of Data Science
- Data Driven Methods
Check out the full curriculum
Visit programme websiteKey information
Duration
- Full-time
- 12 months
- Part-time
- 24 months
Start dates & application deadlines
- Starting
- Apply before
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- Starting
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Language
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Credits
Delivered
Campus Location
- Guildford, United Kingdom
Disciplines
Finance Data Science & Big Data View 406 other Masters in Data Science & Big Data in United KingdomExplore more key information
Visit programme websiteWhat students do after studying
Academic requirements
English requirements
Prepare for Your English Test
AI-powered IELTS feedback. Clear, actionable, and tailored to boost your writing & speaking score. No credit card or upfront payment required.
- Trusted by 300k learners
- 98 accuracy using real exam data
- 4.9/5 student rating
Other requirements
General requirements
- A minimum of a 2:2 in a relevant UK honours degree, or a recognised equivalent international qualification.
- Your qualification should demonstrate basic knowledge and understanding in calculus, linear algebra, probability, and statistics. Specifically, you are suited to this course if your qualification has a reasonable level of mathematical contents in subjects such as mathematics, finance, economics, business, science, engineering, or computing.
- You may also be considered for the course if you have other professional qualification or experience of equivalent standing.
Make sure you meet all requirements
Visit programme websiteTuition Fees
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International Applies to you
Applies to youNon-residents20500 GBP / year≈ 20500 GBP / year -
Domestic Applies to you
Applies to youCitizens or residents10900 GBP / year≈ 10900 GBP / year
Additional Details
Part-time Sep
- UK: 5,500GBP
- Int: 10,300GBP
Living costs
Guildford
The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.
Funding
Check for any work restrictions
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Scholarships Information
Below you will find Master's scholarship opportunities for Financial Data Science.
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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