Mathematics BSc
A*A* in Maths and Further Maths, plus A in a third subject at A level Grade 2 in at A level; graduates earn a median £39,500 three years on.
Typical A level offer
A*A* in Maths and Further Maths, plus A in a third subject at A level Grade 2 in
95% of entrants came with A levels · 92% stay on after year 1 · Warwick course page, Discover Uni
Year 13 · applying
What do you need to get in?
A*A* in Maths and Further Maths, plus A in a third subject at A level Grade 2 intypical A level offer; a*a* in maths and further maths, plus a in a third subject at a level grade 2 in step will be a requirement of offer to applicants who have not taken tmua. applicants who have not achieved the require
Typical offer — the grades most applicants are asked for. Contextual offer: A*A*B with an A* in Mathematics and Further Mathematics, for applicants from under-represented backgrounds.
Warwick course page, read 19 September 2026 · Discover Uni entry profile
Who actually got in: 95% with A levels, 5% with the IB. 73% arrived with 208 or more UCAS tariff points — roughly A*A*A or better. Based on 240 entrants.
UCAS tariff points — a points scale for grades: A* = 56, A = 48, so A*A*A = 160. Entrants’ totals include extra subjects.
Other qualifications4
| Qualification | Typical offer | Required subjects |
|---|---|---|
| IB | 39 points39 with 6 in three Higher Level subjects to include Mathematics ('Analysis and Approaches' only) Grade 2 in STEP will be a requirement of offer to applicants who have not taken TMUA. Applicants who ha | 6 in three Higher Level subjects to include Mathematics |
| BTEC | —We welcome applications from students taking a BTEC alongside A level Mathematics and Further Mathematics. | — |
| Advanced Highers | A1 in Advanced Higher Mathematics (C847), plus grades A2 in an additional AdvancA1 in Advanced Higher Mathematics (C847), plus grades A2 in an additional Advanced Higher and A2 in Higher Mathematics (C847) Grade 2 in STEP will be a requirement of offer to applicants who have not | — |
| Access | 45 Credits at Level 3, including Distinction in 33 Level 3 credits and Merit in We will consider applicants returning to study who are presenting a QAA-recognised Access to Higher Education Diploma on a case-by-case basis. Typically, we require 45 Credits at Level 3, including Di | — |
Years 1–3
What do you study?
9compulsory modules in year 1
Compulsory modules this year: mathematics & statistics 93% · digital & ict skills 3% · transversal skills 3% · language & communication 1%.
Module — one course unit, usually a term or a year long; “core” means everyone takes it. One UK credit is about ten hours of study; a full year is 120 credits.
Warwick course page · optional modules vary by year
Year 1 · 9 core · 100 credits ≈ 1,000 hours
- Mathematics by Computer
What you learn (7)
- write basic Python programs using core syntax constructs
- produce plots of data, curves and surfaces using Python
- perform vector and matrix computations using Python
- apply Python tools to manipulate symbolic algebra and solve equations
- organise tasks and responsibilities within a team project
- investigate a mathematical topic using independent research methods
- present findings clearly to an audience
- Foundations
What you learn (4)
- apply properties of number systems to solve problems
- use set notation and quantifiers to express statements
- describe functions and relations using formal mathematical language
- apply different proof techniques to mathematical statements
- Analysis 2
What you learn (8)
- determine whether a function is differentiable at a point
- compute higher-order derivatives of a function
- describe key properties of differentiable functions
- construct a Taylor series expansion for a function
- apply Taylor's theorem to estimate approximation error
- determine when a function can be represented by a power series
- use upper and lower sums to evaluate integrability
- apply the fundamental theorem of calculus to evaluate integrals
- Analysis 1
What you learn (6)
- describe key properties of the real number system
- explain the meaning and use of the symbol for infinity
- determine the limit of a sequence or series
- distinguish between conditional and absolute convergence of series
- identify properties of continuous functions
- identify properties of absolutely continuous functions
- Methods of Mathematical Modelling 2
What you learn (13)
- evaluate scalar-valued functions of several variables
- evaluate vector-valued functions of several variables
- describe parametric representations of curves
- describe parametric representations of surfaces
- apply coordinate transformations to mathematical expressions
- explain the relationships linking line, surface and volume integrals
- evaluate line, surface and volume integrals using integral theorems
- compute partial derivatives and gradients of multivariable functions
- compute the Jacobian and directional derivative of a function
- compute the divergence and curl of a vector field
- interpret the geometric meaning of a multivariable Riemann integral
- integrate functions over simple regions
- justify changes to area and volume elements under coordinate conversion
- Methods of Mathematical Modelling 1
What you learn (12)
- describe the stages involved in constructing a mathematical model
- formulate a simple mathematical model for a given situation
- analyse the behaviour of a simple mathematical model
- apply scaling and non-dimensionalisation to simplify a model
- apply linear stability analysis to identify dominant dynamics
- explain which factors drive the behaviour of a dynamical system
- solve first order ordinary differential equations
- solve second order ordinary differential equations
- interpret the qualitative behaviour of solutions to differential equations
- solve simple difference equations
- relate difference equations to their continuous differential equation counterparts
- describe basic techniques for numerically approximating solutions
- Algebra 2
What you learn (12)
- explain the concept of a vector space
- determine whether a set of vectors is linearly independent
- identify a basis and calculate the dimension of a vector space
- describe the properties of a linear transformation
- perform row and column operations to reduce a matrix
- apply matrix reduction to solve systems of linear equations
- calculate the determinant of an n by n matrix
- compute cofactors and adjoint matrices
- explain how determinants and adjoints determine solutions of linear systems
- compute eigenvalues and eigenvectors of a matrix
- interpret the geometric meaning of eigenvalues and eigenvectors
- describe linear transformations between euclidean spaces
- Algebra 1
What you learn (9)
- define a group using its axioms
- define a group homomorphism
- identify examples of dihedral and cyclic groups
- manipulate elements of the symmetric group as products of permutations
- determine the order of an element in a group
- define different types of ring
- identify examples of rings such as number sets, polynomials and integers modulo n
- manipulate polynomials over integers, real and complex numbers
- identify the unit group of a ring, including integers modulo n
- Introduction to Probability
What you learn (9)
- apply standard techniques to solve probability problems
- describe experiments involving random outcomes
- interpret random experiments using mathematical probability
- explain the concept of conditional probability
- explain the concept of statistical independence
- apply probability distribution theory to random variables
- calculate expectation, variance and covariance of random variables
- select suitable probability distributions for given problems
- construct probability models to represent real problems
Year 2 · 5 core, 2 optional · 55 credits ≈ 550 hours
- Norms, Metrics and Topologies
What you learn (11)
- describe fundamental definitions of normed, metric and topological spaces
- apply key theorems relating to normed, metric and topological spaces
- perform calculations involving norms, metrics and topological structures
- relate the open-set definition of continuity to classical continuity notions
- apply continuity concepts to analyse open and closed sets
- describe core definitions of compactness, connectedness and completeness
- apply theorems concerning compactness, connectedness and completeness
- carry out calculations involving compactness, connectedness and completeness
- analyse relationships among compactness, connectedness and completeness
- examine how continuous maps preserve compactness, connectedness and completeness
- apply these topological properties to solve simple problems
- Scientific Communication
What you learn (10)
- write mathematical arguments clearly using correct notation
- structure mathematical proofs and explanations in a logical sequence
- deliver a structured oral presentation on a technical topic
- design visual aids that support a scientific talk
- write python scripts to solve computational problems
- debug and test python code for correctness
- locate and evaluate relevant academic sources on a topic
- plan a small research project with defined objectives
- apply time-management strategies to meet deadlines
- collaborate effectively within a team to achieve shared goals
- Methods of Mathematical Modelling 3
What you learn (5)
- apply physical laws to derive partial differential equations
- classify different types of partial differential equations
- distinguish characteristic features of each pde type
- solve main types of pdes on bounded domains
- explain how solution properties depend on pde type
- Algebra 3
What you learn (4)
- describe core constructions in group theory
- describe core constructions in ring theory
- classify groups and rings according to given properties
- construct examples of groups and rings satisfying specified conditions
- Analysis 3
What you learn (9)
- distinguish between uniform and pointwise convergence of function sequences
- describe properties satisfied by the limit function of a convergent sequence
- determine continuity of the limit of a uniformly convergent function sequence
- evaluate differentiability and integrability of a uniformly convergent sequence's limit
- apply the Cauchy-Riemann equations to test complex differentiability
- manipulate complex power series to determine convergence and sums
- compute contour integrals of complex functions along given paths
- apply Cauchy's integral formulas to solve complex analysis problems
- represent the derivative of a multivariable function as a linear map
2 optional modules
- Mathematical Economics 1A
What you learn (2)
- explain the core tools and concepts of game theory
- apply game theory tools to solve varied economic problems
- Mathematical Economics 1B
What you learn (4)
- explain the role of competitive markets in achieving pareto optimal allocations
- apply simple formal assumptions to analyse core economic problems
- identify limitations of established economic models
- describe recent developments in frontier economic research
Year 3 · 0 core, 20 optional
20 optional modules
- Complexity of Algorithms
What you learn (7)
- describe different complexity classes of computational problems
- distinguish between problems belonging to different complexity classes
- apply formal methods to prove a problem is solvable
- apply formal methods to prove a problem is unsolvable
- prove formal bounds on the time required to solve a problem
- prove formal bounds on the memory required to solve a problem
- design simplified versions of computationally hard problems that are easier to solve
- Computer Graphics
What you learn (4)
- explain the mathematical foundations of geometric transformations
- describe techniques for modelling three-dimensional objects
- describe techniques used to approximate realistic image generation
- explain how graphics programming standards implement rendering techniques
- Introduction to Secondary Mathematics Teaching
What you learn (5)
- evaluate key issues in school mathematics education
- reflect critically on debates relevant to teaching mathematics
- reflect critically on personal practice in teaching mathematics
- apply learning theories to mathematics teaching practice in schools
- demonstrate professional skills to support pupils' mathematics learning
- Principles of Finance (for Finalists)
What you learn (16)
- differentiate systematic risk from non-systematic risk
- compare consequences of holding each risk type for investors
- calculate optimal portfolios of risky securities under given conditions
- evaluate theoretical models linking risk and expected return
- evaluate the relationship between bond prices and interest rates
- evaluate links between asset prices and derivative prices
- construct alternative hypotheses explaining the term structure of interest rates
- assess the practical implications of competing term structure theories
- critique empirical tests of the efficient markets hypothesis
- combine multiple theoretical frameworks to analyse complex investment problems
- justify the choice of a particular financial model for a given scenario
- evaluate shortcomings of existing financial theoretical models
- propose adaptations to models for specific market conditions
- compare empirical findings against theoretical predictions in finance
- formulate explanations for discrepancies between theory and evidence
- present complex financial ideas clearly to an audience
- Measure Theory
What you learn (4)
- explain the foundational concepts of abstract measure theory
- construct Lebesgue measure on the real line
- construct Lebesgue measure in n-dimensional Euclidean space
- outline advanced topics within measure theory
- Fractal Geometry
What you learn (5)
- describe explicit constructions of fractal sets
- identify different notions of dimension for fractal sets
- calculate estimates of fractal dimension values
- quantify the degree of fractal irregularity of a set
- relate fractal sets and dimension to other mathematical fields
- Galois Theory
What you learn (14)
- derive the formula for solving cubic equations by radicals
- outline the method for solving quartic equations by radicals
- identify the characteristic of a given field and its prime subfield
- represent a field extension as a vector space over its base field
- factorise polynomials over a field using ideal theory in k[x]
- prove that trisecting an arbitrary angle with straight-edge and compass is impossible
- prove the existence and uniqueness of splitting fields for a polynomial
- identify groups of field automorphisms associated with an extension
- apply the Galois correspondence to relate subgroups and subfields
- construct radical field extensions for given equations
- determine whether a group is soluble
- evaluate whether an equation is solvable by radicals using group solubility
- describe the structure of finite fields
- construct finite fields of given order
- Introduction to Topology
What you learn (4)
- identify topological invariants used to distinguish spaces
- apply topological invariants to differentiate between spaces
- describe methods for constructing spaces by gluing
- construct examples of spaces satisfying specified topological properties
- Mathematics of Machine Learning
What you learn (5)
- identify a suitable optimisation and modelling approach for a machine learning problem
- analyse optimisation algorithms by computational time and space complexity
- evaluate optimisation algorithms in terms of statistical accuracy
- implement a basic neural network architecture
- apply a neural network to a pattern recognition task
- Problem Solving with Python
What you learn (4)
- apply a structured problem-solving framework to mathematical tasks
- use Python to perform mathematical calculations
- create visualisations in Python to support mathematical solutions
- evaluate the effectiveness of one's own problem-solving approach
- Philosophy of Mathematics
What you learn (5)
- outline the historical development of major approaches to the philosophy of mathematics
- relate philosophical questions about mathematics to the foundations of mathematics
- critique arguments presented in support of different theories of mathematics
- explain methodological issues arising in the philosophy of mathematics
- distinguish between philosophical and mathematical approaches to a problem
- The Earth and its Atmosphere
What you learn (5)
- describe the internal structure of the earth
- identify experimental and observational methods used to investigate the earth's interior
- explain how the earth's atmosphere evolved over time
- describe dynamic atmospheric processes such as precipitation and global air circulation
- evaluate how human activity affects the earth and its atmosphere
- Plasma Physics and Fusion
What you learn (10)
- analyse single particle motion in electromagnetic fields
- apply the plasma approximation to describe collective behaviour
- describe the causes of fluid instabilities in plasmas
- describe micro-instabilities and their effect on confinement
- relate plasma instabilities to confinement devices and astrophysical systems
- explain how electromagnetic waves interact with plasma particles
- analyse wave absorption and dispersion phenomena in plasmas
- explain how plasma physics constraints influence fusion reactor design
- explain methods used to heat fusion plasmas
- explain mechanisms of plasma confinement and stability in fusion systems
- Galaxies and Cosmology
What you learn (10)
- describe the structure of the milky way galaxy
- classify galaxy types within the wider galaxy population
- explain the physics underlying observational techniques used to study galaxies
- discuss unresolved questions concerning galactic nuclei
- evaluate the contribution of dark matter to galaxy behaviour
- evaluate the role of interstellar dust in galactic observations
- explain how observational data constrain cosmological models
- explain how model universes evolve over time
- relate energy density components to the evolution of model universes
- discuss discrepancies between cosmological theory and observational evidence
- Black Holes, White Dwarfs and Neutron Stars
What you learn (7)
- identify key processes generating electromagnetic radiation in astrophysical objects
- identify key processes generating gravitational waves in astrophysical objects
- calculate physical parameters of astrophysical systems from observational data
- describe how black holes form and evolve in isolated and binary systems
- describe how neutron stars form and evolve in isolated and binary systems
- describe how white dwarfs form and evolve in isolated and binary systems
- describe techniques used to detect and observe gravitational waves
- Designed Experiments
What you learn (8)
- differentiate between types of experimental design
- judge the efficiency and usefulness of a given design
- explain the fundamental concepts underlying designed experiments
- construct a design matrix for a simple experiment
- calculate parameter estimates from an experimental design matrix
- carry out an analysis of variance for standard experimental designs
- apply diagnostic checks to results of a designed experiment
- formulate an optimal or robust solution to a practical design problem
- Medical Statistics
What you learn (5)
- describe the contribution of statistical methods to medical research
- identify principles of good statistical practice in clinical studies
- apply generalised linear models to analyse medical data
- apply survival analysis techniques to medical data
- interpret results from generalised linear models and survival analysis
- Introduction to Mathematical Finance
What you learn (8)
- solve mean-variance portfolio optimisation problems
- describe the capital market line concept
- describe preference orders used by financial investors
- solve simple utility maximisation problems
- explain monetary measures of financial risk
- calculate value at risk for a given distribution
- calculate expected shortfall for a given distribution
- describe self-financing strategies and no-arbitrage conditions
Year 4 · 0 core, 2 optional
2 optional modules
- Analytic Number Theory
What you learn (6)
- explain key properties of the Riemann zeta function
- derive the prime number theorem from zeta function theory
- relate zeros of the zeta function to exponential sums
- state the riemann hypothesis
- apply advanced analytic number theory concepts to novel problems
- integrate real and complex analysis techniques within number theory problems
- Brownian Motion
What you learn (6)
- apply the martingale property to derive wald's lemmas
- construct brownian motion from its defining properties
- explain the key properties of brownian motion
- apply brownian motion as a continuous-time continuous-state markov process
- derive convergence results using the random walk embedding
- translate one-dimensional brownian motion properties to higher dimensions
“What you learn” restates each module’s published learning outcomes in our own words, as short skill statements in the same form as the GCSE and A level curriculum, with the help of an AI model; fields of knowledge follow the twelve fields of the knowledge sphere. The university’s module page, linked from each title, is the authoritative description.
After graduating
Where does it lead?
£39,500median pay three years after graduating
Lower quarter£29k
Median£40k
Upper quarter£51k
Median — the middle earner: half earned more, half less. Pay is for graduates of this subject at this university who finished in 2016-18, not adjusted for inflation; based on 325 graduates.
Discover Uni dataset (HESA and Office for Students, CC BY 4.0, contains HESA data); earnings from the Longitudinal Education Outcomes data (Department for Education) · aggregation level 14, 13, 23
Half of graduates earned between £29,000 and £51,000. Five years on, the median is £53,000. 89% were in work or further study 15 months after finishing; 85% of those in work were in professional or managerial jobs.
All outcome figures7
| Measure | Value | Based on |
|---|---|---|
| Continue after year 18% left | 92% | 195 |
| In work or study, 15 months on13% studying | 89% | 125 |
| Professional or managerial job | 85% | 90 |
| Pay 15 months on, median | £35,500 | 120 |
| Pay 3 years on, median | £39,500 | 325 |
| Pay 5 years on, median | £53,000 | 365 |
Money
What does it cost?
£10,050a year for UK students, 2027/28 entry
Tuition fee loan — paid straight to the university; repayments start the April after you leave, at 9% of income above the threshold. UK fees are capped by government and rise with inflation; placement and study-abroad years are usually charged at a lower rate.
Warwick fees page · source
About £30,150 in fees over 3 years, covered by a tuition fee loan you repay only when earning above the threshold.
National Student Survey 2025-26
What do students say?
90%agreed the course was good overall (question 26)
NSS — a yearly survey of final-year students at every UK university; 67% of this course’s final year answered. Small groups can swing a lot year to year.
National Student Survey, via Discover Uni · 100 students answered
Highest: 99% agreed on question 21; lowest: 63% on question 14.
All questions26
| Question | Agree |
|---|---|
| Question 1 | 96% |
| Question 2 | 81% |
| Question 3 | 95% |
| Question 4 | 93% |
| Question 5 | 91% |
| Question 6 | 94% |
| Question 7 | 86% |
| Question 8 | 87% |
| Question 9 | 79% |
| Question 10 | 80% |
| Question 11 | 95% |
| Question 12 | 92% |
| Question 13 | 76% |
| Question 14 | 63% |
| Question 15 | 96% |
| Question 16 | 89% |
| Question 17 | 93% |
| Question 18 | 96% |
| Question 19 | 93% |
| Question 20 | 88% |
| Question 21 | 99% |
| Question 22 | 96% |
| Question 23 | 89% |
| Question 24 | 72% |
| Question 25 | 71% |
| Question 26 | 90% |
Question texts are published by the Office for Students; the dataset carries only the question numbers.
Modules, entry requirements and fees are facts read from University of Warwick’s course page on 2026-09-19 and may change; the university’s page is authoritative. Descriptions are not reproduced. Outcome figures are from the Discover Uni dataset. University of Warwick is a trade mark of the university; sch.today is independent of it.