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Imperial College London · London

BSc Mathematics

UndergraduateMathematics & Physics

Covers core pure and applied mathematics including algebra, analysis, probability and statistics, developing rigorous reasoning. Suits students with very strong A-level maths aiming for quantitative careers or further study.

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Funding informationThis university has scholarship information recorded.

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Sri Lankan student planning

Four checks before you shortlist this course.

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

Sri Lankan national school qualifications are not listed among Imperial's accepted UG qualifications; courses typically require A-levels (A*AA to A*A*A) or IB 39–41.

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02English evidence

IELTS or an alternative

7.0 overall, 6.5 in each element (Imperial 'higher' level)

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03Funding

Scholarship possibilities

Scholarship or tuition-discount information is recorded for this university; eligibility may depend on course and intake.

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04Full financial plan

Beyond the tuition fee

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This tool is an early planning guide, not an offer, admissions decision or visa assessment. The university decides admission after reviewing your complete application.

Scholarship information

Potential funding at Imperial College London

For 2027 entry Imperial is offering at least 300 Imperial Inspires scholarships worth £15,000 per year for international (Overseas-fee) students on undergraduate and selected postgraduate taught courses in Engineering, Natural Sciences, Medicine and the Business School.

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 BSc Mathematics

Covers core pure and applied mathematics including algebra, analysis, probability and statistics, developing rigorous reasoning. Suits students with very strong A-level maths aiming for quantitative careers or further study.

This 36-month undergraduate route concentrates on develop advanced quantitative and analytical methods, model complex systems and interpret evidence, apply theory through computation, experiments or projects. 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

  • Develop advanced quantitative and analytical methods.
  • Model complex systems and interpret evidence.
  • Apply theory through computation, experiments or projects.

Skills development

Capabilities you can build

  • Critical thinking
  • Research and evidence use
  • Professional communication
  • Independent project work

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 study and progressively more complex assignments or projects.
  • 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 beginning higher education who want to build knowledge, practical capability and graduate-level skills over time. 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:

  • Quantitative analyst
  • Data or modelling specialist
  • Research scientist
  • Technical consultant

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.

36 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.

  1. 01
    Introduction to University MathematicsPublished course content
  2. 02
    Analysis 1Published course content
  3. 03
    Linear Algebra and GroupsPublished course content
  4. 04
    Calculus and ApplicationsPublished course content
  5. 05
    Probability and StatisticsPublished course content
  6. 06
    Introduction to ComputationPublished course content
  7. 07
    An Introduction to Applied MathematicsPublished course content
  8. 08
    Individual Research ProjectPublished course content
  9. 09
    Linear Algebra and Numerical AnalysisPublished course content
  10. 10
    Analysis 2Published course content
  11. 11
    Multi-variable Calculus and Differential EquationsPublished course content
  12. 12
    Group Research ProjectPublished course content
  13. 13
    I-Explore modulePublished course content
  14. 14
    Groups and RingsPublished course content
  15. 15
    Lebesgue Measure and IntegrationPublished course content
  16. 16
    Probability for StatisticsPublished course content
  17. 17
    Statistical Modelling 1Published course content
  18. 18
    Partial Differential Equations in ActionPublished course content
  19. 19
    Principles of ProgrammingPublished course content
  20. 20
    Classical MechanicsPublished course content
  21. 21
    Advanced Topics in Partial Differential EquationsPublished course content
  22. 22
    Algebra 3Published course content
  23. 23
    Algebraic CombinatoricsPublished course content
  24. 24
    Algebraic Number TheoryPublished course content
  25. 25
    Algebraic TopologyPublished course content
  26. 26
    Applied Complex AnalysisPublished course content
  27. 27
    Applied ProbabilityPublished course content
  28. 28
    Asymptotic MethodsPublished course content
  29. 29
    Bifurcation TheoryPublished course content
  30. 30
    Computational Linear AlgebraPublished course content
  31. 31
    Computational Partial Differential EquationsPublished course content
  32. 32
    Consumer Credit Risk ModellingPublished course content
  33. 33
    Dynamical SystemsPublished course content
  34. 34
    Dynamics of Games and LearningPublished course content
  35. 35
    Finite Elements: Numerical Analysis and ImplementationPublished course content
  36. 36
    Fluid Dynamics 1Published course content

Source checked 19 October 2026. Titles are shown as concise factual course information; the university remains the authoritative source.

View official course contents

Entry requirements

Can I apply?

Academic
A*A*A at A-level, or 39 points IB
Sri Lankan qualifications
Sri Lankan national school qualifications are not listed among Imperial's accepted UG qualifications; courses typically require A-levels (A*AA to A*A*A) or IB 39–41.
English (IELTS)
7.0 overall, 6.5 in each element (Imperial 'higher' level)

Not sure you qualify? Send us your results — we’ll tell you honestly, free.

How we help

Support, clearly agreed.

  1. We check your eligibility and documents.
  2. We prepare and submit your application to Imperial College London.
  3. We help you meet any offer conditions and get your CAS.
  4. We guide your Student visa application.

Your initial consultation is free. Any paid professional support begins only after you receive and accept a written service summary explaining the work, fee and terms.

Similar courses at other universities

See all Mathematics & Physics courses →

Course information checked October 2026 from the official course page on imperial.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 Imperial College London before you apply. Global Educational Consultants is an independent consultancy.