BSc Mathematics and Statistics with Data Science

Compulsory modules

Real Analysis I

Explore mathematical analysis concepts including inequalities, sequences, series and functions.

Calculus 

Extend your existing knowledge of calculus into two or more dimensions, exploring techniques of ordinary differential equations of the first and second order and learning how programming has mathematical applications.

Foundations of Mathematics

Gain a solid introduction to fundamental topics in mathematics and develop the necessary skills to study mathematics at university-level. You’ll focus on the concept of sets, functions and various familiar number systems, as well as the importance of proofs and how to construct them.

Linear Algebra 

Learn how to solve systems of linear equations, determine eigenvalues and eigenvectors, and develop the algebra of matrices which are used as a stepping-stone to the more general theory of liner and inner-product spaces.

Mathematical Communication 

Discover the importance of expressing mathematical concepts and results clearly, logically and concisely and how to implement basic problem-solving strategies such as data visualisation, pattern exploration and programming.

Probability and Statistics  

Understand probability and probability distributions, results and techniques for statistical reference and data science, and regression and hypothesis testing.

These are the modules that we currently offer for 2024/25 entry. They may be subject to change as we regularly review our module offerings to ensure they’re informed by the latest research and teaching methods.

Please note that the University cannot guarantee that all optional modules will be available to all students who may wish to take them.

You can also register your details with us to receive information about your course of interest and study and life at the University of Reading.

Compulsory modules

Differential Equations 

Build on your knowledge of ordinary differential equations and explore partial differential equations and their applications. You’ll explore non-constant coefficients, integral and series solutions, Fourier series, the theory of boundary value problems, diffusion equations, wave equations and Laplace’s equation.

Linear Models and Data Analysis 

Gain understanding of the most common models, including multiple linear regression and completely randomised designs, and explore the key principles of planned experiments. Learn how models are applied to practical problems and gain experience of real-life data analysis.

Probability and Statistical Theory 

Uncover the interplay between probability theory and fundamental areas of mathematics, and formulate general real or abstract problems in a probabilistic model.

Numerical Analysis I 

Describe, analyse and implement numerical methods for problems in continuous mathematics, including solution of linear equations and nonlinear scalar equations, interpolation, scalar optimisation and solution of ordinary differential equations.

Mathematical Modelling and Professional Skills

Develop your problem-solving and independent research skills by applying mathematical modelling techniques to solve real-world problems across a broad range of scientific, engineering and economical areas. You’ll also expand your team-working, presentation, career management, technical, verbal and written communication skills.

Optional modules

Algebra 

Understand the concepts of abstract algebra, including groups, rings and fields and the connections between them.

Programming in Python 

Using Python programming languages, develop your skills and knowledge to use current tools in general program designs, development and data science. You’ll also develop transferable professional skills for a variety of fields that use programming. 

Real Analysis II 

Expand your understanding analysis to cover continuity of functions, integration and differentiation.

Mathematical Methods and Physical Applications 

Discover how vector calculus and variational principles are applied to various areas of physics, such as classical mechanics, elements of electromagnetism and diffusion.

These are the modules that we currently offer for 2024/25 entry. They may be subject to change as we regularly review our module offerings to ensure they’re informed by the latest research and teaching methods.

Please note that the University cannot guarantee that all optional modules will be available to all students who may wish to take them.

You can also register your details with us to receive information about your course of interest and study and life at the University of Reading.

Compulsory modules

Advanced Statistical Modelling

Develop an understanding of situations in which different models are likely to be appropriate, learning more about generalised linear models, repeated measurement data, and traditional and modern approaches to data analysis.

Methods of Machine Learning

Gain familiarity with the range of methods used in statistical machine learning and demonstrate how these are used in research and industry. You’ll have the opportunity to implement machine learning methods using statistical software and interpret and communicate your findings.

Portfolio of Projects

Conduct a series of projects on mathematical or statistical topics and develop your technical and professional skills.

Optional modules

Probability and Measures

Explore measure theory, integration and measure theoretic probability.

Complex Analysis 

Gain an introduction to complex analysis and how its functions can be represented, exploring aspects such as power series, exponential functions, trigonometric functions and hyperbolic functions.

Metric Spaces and Functional Analysis

Study analysis from a more general perspective based on the concepts of distance, including Normed, metric spaces, the concepts of convergence, continuity, compactness and completeness.

Applied Stochastic Processes 

Learn how to solve problems using stochastic processes and concepts from a variety of applications, including molecular motion, population dynamics, weather and finances.

Numerical Analysis II

Motivate, develop and analyse a range of algorithms for the approximate solution of problems of continuous mathematics and techniques in numerical linear algebra.

Number Theory and Cryptography

Explore a range of topics within number theory and cryptography, including the RSA cryptosystem and error correcting codes.

Dynamical Systems and Applications

Analyse dynamical systems and their applications to real-world problems. You’ll explore systems of linear and nonlinear differential equations, and understand how they’re applied to biological issues such as population growth, cell systems, and the spread of infectious diseases.

Partial Differential Equations and Applications

Examine partial differential equations and how they appear in practical applications and natural phenomena, in particular fluid mechanics, water waves and wave scattering theory.

Asymptotic Methods

Discover the basic ideas of asymptotic analysis and further develop your skills in solving a range of problems involving nonlinear equations, integrals and differential equations.

Image Analysis and Visual Intelligence

Gain theoretical and practical knowledge of image analysis and computer vision by using real-world applications. You’ll develop professional skills such as problem solving, team-working, critical analysis, creativity and technical report writing for various audiences. 

Data Integration and Information Visualisation 

Transform raw data into visual insights to develop your understanding of data integration. You’ll work with peers to critically reflect on design process and outcomes, using commercial software tools and writing professionally for software design documents. 

Computer Graphics, Games and Virtual Reality

Study virtual reality in terms of scientific issues, application areas and strengths and weaknesses of the technology. You’ll use software to design virtual worlds and/or games and learn techniques for their creation using computer graphics.

Mathematical Physics

Explore the core topics of mathematical physics, in particular Hamiltonian formulation of classical mechanics, quantum mechanics and statistical mechanics. 

Text Mining and Natural Language Processing

Study the field of text mining and natural language processing, focusing on the theories and practice of processing text data from the aspects of lexicons, syntactics and semantics.

Blockchain and Security

Deploy blockchain for various applications, gaining a theoretical and practical understanding that develops your critical thinking, writing and design skills. You’ll reflect on rationale, benefits and potential societal and environmental impacts, specifically carbon emissions. 

These are the modules that we currently offer for 2024/25 entry. They may be subject to change as we regularly review our module offerings to ensure they’re informed by the latest research and teaching methods.

Please note that the University cannot guarantee that all optional modules will be available to all students who may wish to take them.

You can also register your details with us to receive information about your course of interest and study and life at the University of Reading.