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Four-year bachelor special, honours or professional degree from a recognised university: final mark 60% is comparable to a UK 2:1 and 55% to a UK 2:2
Check my qualifications →Heriot-Watt University · Edinburgh
MSc Data Science
Teaches how to collect, analyse and communicate insights from large, complex datasets, covering data mining, machine learning and statistical modelling, finishing with a dissertation project. Aimed at graduates with a computing background; the programme is BCS-accredited.
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IELTS or an alternative
6.0 overall, no band below 5.5
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Scholarship information
Potential funding at Heriot-Watt University
Some masters programmes (for example MSc Data Science) offer an Academic Excellence Scholarship of a £2,000 tuition fee reduction to the strongest applicants; other scholarships are listed in the university's scholarship search.
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 Data Science
Teaches how to collect, analyse and communicate insights from large, complex datasets, covering data mining, machine learning and statistical modelling, finishing with a dissertation project. Aimed at graduates with a computing background; the programme is BCS-accredited.
This 12-month postgraduate route concentrates on data preparation, exploration and visualisation, statistical modelling and machine-learning methods, turning complex evidence into useful 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
- Data preparation, exploration and visualisation
- Statistical modelling and machine-learning methods
- Turning complex evidence into useful decisions
- Machine learning and intelligent systems
Skills development
Capabilities you can build
- Python or analytical programming
- Statistical reasoning
- Data visualisation
- Model evaluation and communication
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 who enjoy combining programming, statistics and problem-solving to extract meaning from complex data. 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:
- Data scientist
- Data analyst
- Business intelligence analyst
- Machine-learning or analytics specialist
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.
16 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.
- 01Data Mining and Machine LearningPublished course content
- 02Statistical Modelling and AnalysisPublished course content
- 03Biologically Inspired ComputationPublished course content
- 04Computer Network SecurityPublished course content
- 05Industrial ProgrammingPublished course content
- 06Software Engineering FoundationsPublished course content
- 07Databases and Information SystemsPublished course content
- 08Introduction to Natural Language ProcessingPublished course content
- 09Big Data ManagementPublished course content
- 10Data Visualisation and AnalyticsPublished course content
- 11Research Methods and Project PlanningPublished course content
- 12Advanced Software EngineeringPublished course content
- 13Digital and Knowledge EconomyPublished course content
- 14Data Engineering PipelinesPublished course content
- 15Distributed & Parallel TechnologiesPublished course content
- 16Masters Project and DissertationPublished course content
Entry requirements
Can I apply?
- Academic
- Second class honours degree (or non-UK equivalent) with substantial computer science and programming content; a 2-year route exists for those without it (September only)
- Sri Lankan qualifications
- Four-year bachelor special, honours or professional degree from a recognised university: final mark 60% is comparable to a UK 2:1 and 55% to a UK 2:2
- English (IELTS)
- 6.0 overall, no band below 5.5
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Course information checked October 2026 from the official course page on hw.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 Heriot-Watt University before you apply. Global Educational Consultants is an independent consultancy.