11312 modules
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MATH6174 2026-27
Likelihood and Bayesian Inference
This module develops methods for conducting inference about parametric statistical models. The techniques studied are general and applicable to a wide range of statistical models, including simple models for identically distributed responses and regression models, as well as many more complex models which may be encountered in other modules. -
MATH6174 2027-28
Likelihood and Bayesian Inference
This module develops methods for conducting inference about parametric statistical models. The techniques studied are general and applicable to a wide range of statistical models, including simple models for identically distributed responses and regression models, as well as many more complex models which may be encountered in other modules. -
MATH6174 2028-29
Likelihood and Bayesian Inference
This module develops methods for conducting inference about parametric statistical models. The techniques studied are general and applicable to a wide range of statistical models, including simple models for identically distributed responses and regression models, as well as many more complex models which may be encountered in other modules. -
PHYS1203 2027-28
Linear Algebra for Physics
Linear algebra is the branch of mathematics focused on linear equations, their solutions, and many topics naturally connected to these, such as matrices, vector spaces, inner products, and more. Physicists use linear algebra to describe an enormous number of phenomena, including some of the most important and fundamental, like normal mode oscillations, particle collisions, stability analysis, and more. This module covers the aspects of linear algebra used most commonly in physics, with examples from mechanics, electricity and magnetism, relativity, and more. The aim of the module is to provide students with an expanded skill set for solving problems in physics, and in the process, to reveal the deep and profound connections between different areas of physics. -
PHYS1203 2025-26
Linear Algebra for Physics
Linear algebra is the branch of mathematics focused on linear equations, their solutions, and many topics naturally connected to these, such as matrices, vector spaces, inner products, and more. Physicists use linear algebra to describe an enormous number of phenomena, including some of the most important and fundamental, like normal mode oscillations, particle collisions, stability analysis, and more. This module covers the aspects of linear algebra used most commonly in physics, with examples from mechanics, electricity and magnetism, relativity, and more. The aim of the module is to provide students with an expanded skill set for solving problems in physics, and in the process, to reveal the deep and profound connections between different areas of physics. -
PHYS1203 2026-27
Linear Algebra for Physics
Linear algebra is the branch of mathematics focused on linear equations, their solutions, and many topics naturally connected to these, such as matrices, vector spaces, inner products, and more. Physicists use linear algebra to describe an enormous number of phenomena, including some of the most important and fundamental, like normal mode oscillations, particle collisions, stability analysis, and more. This module covers the aspects of linear algebra used most commonly in physics, with examples from mechanics, electricity and magnetism, relativity, and more. The aim of the module is to provide students with an expanded skill set for solving problems in physics, and in the process, to reveal the deep and profound connections between different areas of physics. -
MATH1048 2027-28
Linear Algebra I
Linear maps on vector spaces are the basis for a large area of mathematics, in particular linear equations and linear differential equations, which form the basic language of the physical sciences.
This module restricts itself to the vector space R^n to build an intuitive understanding of the concepts of linear algebra and tools for calculations. We begin with the geometry of lines and planes in R^3 and R^n looking at the intuitive concept of vectors on the one hand, and with systems of linear equations on the other. This leads us to matrix algebra, and in particular the inversion of matrices.
One of the pre-requisites for MATH1049, MATH1057, MATH1058, MATH1060, MATH2013, MATH2045, MATH3087, MATH3033 and MATH3090 -
MATH1048 2025-26
Linear Algebra I
Linear maps on vector spaces are the basis for a large area of mathematics, in particular linear equations and linear differential equations, which form the basic language of the physical sciences.
This module restricts itself to the vector space R^n to build an intuitive understanding of the concepts of linear algebra and tools for calculations. We begin with the geometry of lines and planes in R^3 and R^n looking at the intuitive concept of vectors on the one hand, and with systems of linear equations on the other. This leads us to matrix algebra, and in particular the inversion of matrices.
One of the pre-requisites for MATH1049, MATH1057, MATH1058, MATH1060, MATH2013, MATH2045, MATH3087, MATH3033 and MATH3090 -
MATH1048 2026-27
Linear Algebra I
Linear maps on vector spaces are the basis for a large area of mathematics, in particular linear equations and linear differential equations, which form the basic language of the physical sciences.
This module restricts itself to the vector space R^n to build an intuitive understanding of the concepts of linear algebra and tools for calculations. We begin with the geometry of lines and planes in R^3 and R^n looking at the intuitive concept of vectors on the one hand, and with systems of linear equations on the other. This leads us to matrix algebra, and in particular the inversion of matrices.
One of the pre-requisites for MATH1049, MATH1057, MATH1058, MATH1060, MATH2013, MATH2045, MATH3087, MATH3033 and MATH3090 -
MATH1049 2027-28
Linear Algebra II
Building on the intuitive understanding and calculation techniques from Linear Algebra I, this module introduces the concepts of vector spaces and linear maps in an abstract, axiomatic way. In particular, matrices are revisited as the representation of a linear map in a specific basis. We furthermore introduce the concept of bases of vector spaces and study diagonalisation of linear maps.
We apply the abstract theory both in the context of Rn (as seen in Linear Algebra I) and in the context of function spaces; these are particularly important in the study of linear differential equations and hence for instance in physical sciences; for example we look at the derivative operator on the space of polynomial functions.
One of the pre-requisites for MATH2003, MATH2014, MATH2045, MATH3033, MATH3076 and MATH3090