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Department of Mathematics

Mathematics (with an industrial placement year)

(MMath) Mathematics (with an industrial placement year)

Entry for 2025

FHEQ level

This course is set at Level 7 (Masters) in the national Framework for Higher Education Qualifications.

Course learning outcomes

Knowledge and Understanding: By the end of the programme a successful student is expected to be able to: demonstrate in depth knowledge and understanding of a core of analysis, algebra, applied mathematics, probability, statistics and, where appropriate, other sciences with a strong mathematical component, much of which is at (or is informed by) the forefront of the discipline; demonstrate knowledge and understanding of advanced topics, depending on his or her own choice.
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Intellectual Skill: By the end of the programme a successful student is expected to be able to: demonstrate ability to understand and use mathematical arguments and deductive reasoning; demonstrate awareness of the importance of mathematical and statistical assumptions and awareness of their use.

Intellectual Skill: By the end of the programme a successful student is expected to be able to understand and critically evaluate current research and, where appropriate, to suggest new ideas."

Practical Skills: By the end of the programme a successful student is expected to be able to: demonstrate competence in the use of mathematical methods and techniques in problem solving and modelling; explore and solve advanced mathematical problems, by selecting appropriate techniques; demonstrate knowledge and understanding of the process of mathematical or statistical modelling; exhibit advanced skills of numeracy, involving use of quantitative concepts and arguments, where appropriate, at all stages of work.

Transferable Skills: By the end of the programme a successful student is expected to be able to: communicate scientific information effectively, orally and in writing; work and learn independently, including taking responsibility for their own learning, time-management and organisation

Transferable Skills: By the end of the programme a successful student is expected to be able to: take decisions in complex and unpredictable contexts; apply a range of mathematical, computational, numerical and statistical skills.

Full-time course composition

YearTermStatusModuleCreditsFHEQ level
1Autumn SemesterCoreAnalysis 1 (G5135)154
  CoreDiscrete Mathematics (G5136)154
  CoreFundamentals of Mathematics (G5133)154
  CoreLinear Algebra 1 (G5134)154
 Spring SemesterCoreAnalysis 2 (G5139)154
  CoreComputational Mathematics (G5137)154
  CoreLinear Algebra 2 (G5138)154
  CoreNumber Theory (G5140)154
YearTermStatusModuleCreditsFHEQ level
2Autumn SemesterCoreAlgebra (G5144)155
  CoreCalculus of Several Variables (G5141)155
  CoreIntroduction to Probability (G5143)155
  CoreOrdinary Differential Equations (G5142)155
 Spring SemesterCoreDifferential Equations with Modelling (G5148)155
  CoreNumerical Analysis (G5147)155
  CoreProbability and Statistics (G5146)155
  CoreReal Analysis (G5145)155
YearTermStatusModuleCreditsFHEQ level
3All Year TeachingCoreProfessional Placement Year Mathematics (GP100)1205
YearTermStatusModuleCreditsFHEQ level
4Autumn SemesterCorePartial Differential Equations (G1114)156
  OptionApplied Numerical Analysis (L.6) (G1110)156
  Communicating STEM (899S4)156
  Computing for Data Analytics and Finance (L6) (G5219)156
  Data Science Research Methods (L6) (G5222)156
  Financial Mathematics (L.6) (G5124)156
  Functional Analysis (L.6) (G1029)156
  Introduction to Mathematical Biology (L6) (G5106)156
  Linear Statistical Models (L6) (G1107)156
  Probability Models (L6) (G1100)156
 Spring SemesterCoreMaths Matters (Project) (G5270)156
  OptionComplex Analysis (L6) (G5261)156
  Cryptography (L.6) (G1032)156
  Dynamical Systems (L6) (G5126)156
  Machine Learning and Statistics for Health (L6) (G5221)156
  Monte Carlo Simulations (L6) (G5220)156
  Numerical Solution of Partial Differential Equations (L.6) (G5217)156
  Researching STEM (899S5)156
  Statistical Inference (L.6) (G5216)156
YearTermStatusModuleCreditsFHEQ level
5Autumn SemesterOptionApplied Numerical Analysis (L.7) (852G1)157
  Data Science Research Methods (L7) (970G1)157
  Financial Mathematics (L.7) (G5078)157
  Functional Analysis (L.7) (851G1)157
  Introduction to Mathematical Biology (L7) (977G1)157
  Linear Statistical Models (L7) (971G1)157
  Probability Models (L7) (973G1)157
 Autumn & Spring TeachingCoreMMath Project (846G1)457
 Spring SemesterOptionComplex Analysis (L7) (975G1)157
  Dynamical Systems (L7) (976G1)157
  Financial Portfolio Analysis (849G1)157
  Machine Learning and Statistics for Health (L7) (974G1)157
  Monte Carlo Simulations (L7) (865G1)157
  Numerical Solution of Partial Differential Equations (L.7) (845G1)157
  Statistical Inference (L.7) (867G1)157

Please note that the University will use all reasonable endeavours to deliver courses and modules in accordance with the descriptions set out here. However, the University keeps its courses and modules under review with the aim of enhancing quality. Some changes may therefore be made to the form or content of courses or modules shown as part of the normal process of curriculum management.

The University reserves the right to make changes to the contents or methods of delivery of, or to discontinue, merge or combine modules, if such action is reasonably considered necessary by the University. If there are not sufficient student numbers to make a module viable, the University reserves the right to cancel such a module. If the University withdraws or discontinues a module, it will use its reasonable endeavours to provide a suitable alternative module.