Mathematics

Mathematics is one of the most rigorous and transferable disciplines a student can study, developing the capacity for logical reasoning, abstract thinking and precise problem-solving that is valued across an enormous range of careers. Pure mathematics explores the foundations of number theory, algebra, analysis and geometry, asking what is true and why, with a rigour that demands careful proof. Applied mathematics uses these foundations to model real-world phenomena in physics, engineering, finance, biology and beyond.

Statistics provides the tools to reason about uncertainty, to analyse data and to draw valid inferences from evidence.

At Nottingham Trent University you will study this three-year full-time programme, developing a thorough grounding in the core areas of the discipline before exploring the areas that interest you most. The course is supported by staff who are committed to making the journey through challenging material achievable and rewarding, and the applied orientation of much of NTU's teaching ensures that the mathematics you study is connected to real-world problems and professional applications. The typical entry tariff for this programme is around 104 UCAS points.

You will develop skills in mathematical proof, calculus, linear algebra, differential equations, probability, statistics and numerical methods, learning to think precisely, to construct arguments carefully and to communicate mathematical ideas clearly. These are capabilities that transfer far beyond mathematics itself.

Mathematics graduates are among the most sought-after in the graduate labour market. Careers in data science, financial analysis, actuarial work, software engineering, operations research, teaching, consultancy and many other fields are all accessible. The combination of analytical rigour and quantitative facility that a mathematics degree develops is recognised by employers across finance, technology, healthcare, public policy and manufacturing.

Many graduates also pursue postgraduate study in mathematics, statistics, data science, finance or engineering, deepening specialist expertise before moving into research or specialist professional roles.