You’ll study the basic concepts and standard methods of:

• mathematical notation and proof
• functions
• complex numbers and variables
• solution of equations
• resolution of inequalities
• sequences and series

This module will introduce you to the fundamental concepts of calculus, and you’ll develop some of their applications including basic ordinary differential equations.

You’ll be given an introductory treatment of vectors, matrices, geometry, and discrete maths, and you’ll be introduced to their application to real-world problems.

This module will present the place of mathematics and statistics in society, both historical and contemporary, while introducing some essential study skills. You’ll develop and practise personal and technical skills (for example, self study, teamwork, writing reports and making presentations).

This module will present some basic ideas and techniques of statistics while introducing some essential study skills (for example basic IT, note-taking, study skills for mathematics and statistics).

This module will present some basic ideas and techniques of statistics while introducing some essential study skills, allowing you to develop and practice personal and technical skills (for example, self study, teamwork, analysing data, writing reports and making presentations).

This module will introduce you to the basic ideas of linear algebra, such as matrices and determinants, vector spaces, bases, eigenvalues and eigenvectors. You’ll study various standard methods for solving ordinary differential equations and understand their relevance and the connections with linear algebra.

This module will present the basic ideas, techniques and results for calculus of two or more variables, including partial differentiation and integration over curves, surfaces and volumes.

This module will give a rigorous treatment of convergence of sequences and infinite series of real numbers and of continuity, differentiability and integrability of functions of a real variable, and will illustrate the importance of these concepts in the analysis of problems arising in applications.

This module will present the basic concepts of probability theory and statistical inference, and provide you with the tools to appropriately analyse a given data set and effectively communicate the results of such analysis.

You’ll be introduced to mathematical modelling in a wide variety of contexts. You’ll learn how to employ a variety of tools (including vectors and ODEs) in mathematical modelling.

This module will introduce you to R as both a data-science environment and as a general programming language. You’ll use R to import data and perform exploratory data analysis, including data visualisation. You’ll be introduced to basic concepts in scientific modelling, including parameter exploration, and you’ll be equipped for implementing and debugging simple models in R.

This module will demonstrate the central role linear algebra plays in applied mathematics. You’ll be provided with the tools to solve equations involving matrices. You’ll see how theoretical considerations lead to efficient computational techniques, and gain practical experience of solving linear algebra problems computationally.

This module will introduce and provide understanding of the least squares multiple regression model, general linear model, transformations and variable selection procedures, helping you to understand their importance in contemporary technology.

By the end of the module, you’ll be familiar with, and able to perform in R, multiple linear regression, generalised linear models (Poisson and Negative Binomial), generalised additive models, and penalised regression models.

This module will provide a broad introduction to analytical methods for solving partial differential equations. You’ll develop your understanding and technical skills in this area.

You’ll be introduced to ideas in mathematics and statistics that can be used to model real systems, with an emphasis on the valuation of financial derivatives.

The module places equal emphasis on deterministic analysis (calculus, differential equations) and stochastic analysis (Brownian motion, birth and death processes). In both cases, in addition to theoretical analysis, appropriate computational algorithms are introduced.

The first half of the module introduces general modelling and simulation tools, and the second half focuses on the specific application of valuing financial derivatives, including the celebrated Black-Scholes theory.

This module will present the main results in Functional Analysis, give you an introduction to linear operators on Banach and Hilbert spaces, and study applications to integral and differential equations.

This module will provide you with a range of applied statistical techniques that can be used in professional life. You’ll learn the fundamental principles of statistical modelling through experimental design and multivariate analysis.

This module will present you with the basic theory and practice of finite element methods and polynomial and piecewise polynomial approximation theory.

You'll be introduced to a range of modern statistical methods and practices used in industry, commerce and research, and will develop skills in your application and presentation.

This module will teach the application of mathematical models to a variety of general problems in biology, medicine, and ecology, with many applications drawn from marine population modelling.

You’ll see the application of ordinary differential equations to simple biological and medical problems, the use of mathematical modelling in biochemical reactions, and the application of partial differential equations in describing spatial processes such as cancer growth and pattern formation in embryonic development.

The marine population modelling applications will also introduce you to the use of difference models to represent population processes through applications to fisheries, and the use of coupled ODE system to describe ecosystems.

This module will demonstrate the central role network theory plays in mathematical modelling. You’ll see the intimate connection between linear algebra and graph theory, and use this connection to develop a sound theoretical understanding of network theory. You’ll apply the theory as a tool for revealing structure in networks, and apply the algorithms on a network using computer codes.

You’ll learn new statistical methodology and apply it to real data from medical research studies, with an emphasis on the interpretation of the statistical results in the context of the medical problem being investigated. This skill is necessary for the application of statistics to medical data and differs from the traditional, standard interpretation of statistical textbook problems.

In this module, you'll explore the theoretical underpinnings of education. You'll be encouraged to engage with issues of the nature and the purpose of education, social justice and equality, and practice and policy in relation to ethical and political ideas. Throughout this module, we aim to disrupt and expand your thinking about education. You'll be asked to reflect on your values and beliefs in relation to a range of educational questions and issues and you will be presented with questions designed to challenge and refine your current thinking.

The module will give you opportunities to consider how theoretical underpinnings relate to the classroom; how your developing understanding translates into the education context; and how your own values and beliefs interact with your developing professional identity. Human Rights and Learning for Sustainability together form the basic architecture of this module.

This module aims to develop students as enquiring self-reflective practitioners who are able to work collaboratively to develop skills, knowledge and expertise in an area of professional practice. Students will be supported to develop as autonomous, transformative leaders of change. Across the globe there is a growing call for education systems to be responsive to the increasingly dynamic, complex and fast-changing nature of society. Through this module, students will develop the skills and expertise necessary to respond to the changing circumstances of the learning communities they encounter.

The module will provide active and collaborative opportunities for you to explore how to plan discrete, integrated, and interdisciplinary curricular learning with a particular focus on the teaching of mathematics and general science.

Taught both on campus and in schools, this module will enable you to become an effective teacher through learning pedagogical theory, observing experienced teachers and applying your knowledge and understanding in the practical context.

This module aims to give students an opportunity to apply knowledge and skills in STEM pedagogical methods gained on this as well as other course modules to help learners in a variety of situations and institutions.

This module aims to provide students an opportunity to engage with their peers and learners of STEM in a variety of situations on and off campus. This will give them a real life context in which they can relate their ideas learned in their mathematics curriculum and pedagogy classes.

This module will introduce you to a range of modern statistical methods and practices used in industry, commerce and research, and you'll develop skills in their application and presentation.