Overview

Are you curious about how maths helps to shape the world? Then our applied maths course could be for you.

Course outline and modules

What you’ll learn

Our programme is designed to create graduates with a strong mathematical background oriented towards knowledge and technical skills in demand by the job market.

In your first and second years, you will build a solid foundation of mathematical knowledge by learning core mathematical topics, such as Algebra, Analysis, Calculus, Differential Equations, Geometry and Probability, amongst others. You will also be developing abilities for problem-solving and real-world applications of that knowledge. For instance:

In Probability and Statistics, you will be introduced to the elementary theory of probability and statistics and learn to apply that knowledge using Microsoft Excel to statistically analyse real-world data sets and draw relevant and practical conclusions.

Numerical Algorithms and Programming will provide you with an essential understanding of core concepts in programming, focussing on mathematics applications. You will learn how to formulate algorithms to execute methods and how to implement generic algorithms from a description.

Machine Learning will introduce you to some of the fundamental concepts powering the Artificial Intelligence (AI) revolution. You will learn to address some of the fundamental tasks in the field, how to formulate them, and how to apply machine learning algorithms to manipulate data.

After the second year, you can take two possible routes. You may decide to spend your third year in a paid professional placement, of direct relevance to your studies, or you can start your final year in the programme.

The final year will allow you to choose specialist options, steering the emphasis of your degree. You will be presented with optional modules which capitalise on cutting-edge research carried out within the Mathematics department in the fields of data science, data modelling, machine learning and many others.

Data Science is a fast-growing area of great importance due to the large amount of available data and the penetration of machine learning methods. We offer a cluster of modules to build up this expertise in our graduates. For instance, in Time Series you will study the theory and practice of analysing and forecasting data, acquiring hands-on experience in the analysis and forecasting of real-life economic, financial, physical, and physiological time series. Probability Modelling will equip you with the theoretical and practical probabilistic machine learning tools required for modelling and inferring data. You will be able to carry out classification, regression, forecasting, inference and optimisation tasks that are essential for many application domains. Network Science facilitates a greater understanding of the links between network constituents and how they affect their behaviour. The properties of social networks, the internet as well as electricity grids and communication networks are revealed from mathematical analysis, with an impact on their stability, robustness and efficiency.

Finance is an area in which mathematics plays an important role and we have grouped relevant modules to enable dedicated training in the mathematics of finance. These include the two modules Financial Mathematics, and Portfolio Theory and Options Theory, where you will learn how everyday banking mechanisms like pensions, mortgages, credit cards and financial bonds function as real-life investment and trading instruments. These individual financial assets will then be selectively combined to construct portfolios that can maximise profit in a fluctuating market addressing individual requirements as mathematical constraints.
In In-Game Theory, you will sharpen your strategic thinking by analysing economic and strategic competition in terms of benefits and costs. You will be equipped with intuitive yet powerful methods applicable from the socio-economic world to genetics and evolution.

There are many other options available. For example, you will have the opportunity to learn the basics of Quantum Computing, an exciting new area that is expected to shape the future. Our programme is one of the few in the UK to include quantum computing as part of an undergraduate course in mathematics.

By the end of your course, if you choose the Mathematics Project option, you will have undertaken independent studies to master particular topics and use that knowledge to solve a specific problem. All projects are closely supervised by members of the academic staff with expertise in the topic.

Modules

In the first year of the course, students study fundamental Mathematics modules alongside modules providing basic writing and computing skills.

•    Fundamental Mathematics
•    Vector Algebra and Geometry
•    Mathematical Thinking and Writing
•    Probability and Statistics
•    Probability Distributions
•    Numerical Algorithms and Programming
•    Ordinary Differential Equations
•    Analysis I

Learning, teaching and assessment

Career prospects