Teaches practical data analysis and machine learning techniques and how they support decisions in areas such as healthcare and finance, along with the ethics of data use. Aimed at STEM graduates moving into data roles.
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Check your fitMatch your level, budget, intake and preferences.
Use these as an early planning guide. We will confirm the exact university rules for your qualification and intake before you apply.
01Academic route
Your qualification fit
Bachelor Special degree with good grades from a reputable university (most departments ask for 2:1 or 2:2 equivalent); Bachelor General degree with 2:1 or First also considered; CIMA Chartered Accountancy Diploma considered for direct entry; Pre-Masters available
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Scholarship information
Potential funding at Royal Holloway, University of London
Students living in Sri Lanka receive an automatic £4,000 tuition fee reduction on full-time self-funded masters (Sept 2027/Jan 2028 entry); the International Undergraduate Scholarship gives £3,000 off fees each year for international students achieving BBB at A-level or equivalent.
Eligibility, value, availability and deadlines are decided by the university. Confirm the award for this exact course and intake before relying on it.
Programme overview
A clearer look at MSc Applied Data Science
Teaches practical data analysis and machine learning techniques and how they support decisions in areas such as healthcare and finance, along with the ethics of data use. Aimed at STEM graduates moving into data roles.
This 12-month postgraduate route concentrates on corporate finance and investment decisions, financial markets, risk and valuation, quantitative analysis for business decisions. The course record does not promise a placement, so students should judge it primarily by its curriculum, teaching approach and project opportunities.
Course focus
What you can expect to explore
Corporate finance and investment decisions
Financial markets, risk and valuation
Quantitative analysis for business decisions
Data preparation, exploration and visualisation
Skills development
Capabilities you can build
Financial modelling
Investment appraisal
Risk analysis
Data-informed decision-making
The balance of technical, academic and professional skills depends on the modules and assessments offered for your intake.
Learning experience
How you may learn
Applied work such as case studies, workshops, projects or problem-based tasks.
Independent postgraduate study, critical reading and a dissertation or major project where required.
Assessment may combine coursework, reports, presentations, examinations or projects; the exact balance is set by the university.
Who is this course for?
A strong fit for students interested in how organisations and markets allocate money, value opportunities and manage financial risk. Entry requirements still determine eligibility, and students should compare the official module list with their own career goals before applying.
Career direction
Where it may lead
Relevant career directions may include:
Financial analyst
Investment analyst
Corporate finance associate
Risk or treasury analyst
These are examples, not guaranteed outcomes. Employment depends on your experience, location, professional registration where applicable and the modules completed.
Course contents
Published course content for this programme.
18 curriculum items were captured from the university’s official course page. These may include modules, course units or published curriculum topics, and can change by intake, pathway and availability.
01
Computing for Data AnalysisPublished course content
02
Multi-dimensional Data ProcessingPublished course content
03
Research MethodsPublished course content
04
Applications of Data SciencePublished course content
05
Methods of Visualisation and Exploratory AnalysisPublished course content
06
Ethics in Advanced Computing and Artificial IntelligencePublished course content
07
Individual Project in Applied Data SciencePublished course content
08
Academic IntegrityPublished course content
09
International & EU requirementsPublished course content
Sign up for more informationPublished course content
16
Visit Royal HollowayPublished course content
17
Research and educationPublished course content
18
About usPublished course content
Entry requirements
Can I apply?
Academic
2:2 UK honours degree or equivalent in a STEM subject (the list includes accounting, engineering and sciences)
Sri Lankan qualifications
Bachelor Special degree with good grades from a reputable university (most departments ask for 2:1 or 2:2 equivalent); Bachelor General degree with 2:1 or First also considered; CIMA Chartered Accountancy Diploma considered for direct entry; Pre-Masters available
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More Data Science & AI courses at Royal Holloway, University of London
Course information checked October 2026 from the official course page on royalholloway.ac.uk. The expanded description is original GEC guidance built from the recorded course summary, award level and subject; it does not reproduce a university or partner listing word for word. Exact modules, teaching, assessment, professional recognition, fees, entry requirements and intakes can change. We confirm the latest details with Royal Holloway, University of London before you apply. Global Educational Consultants is an independent consultancy.
MSc Applied Data Science at Royal Holloway, University of London | Fees & Entry | GEC