BSc Applied Mathematics
Entry requirements
A level: from A*A*A* to A*AB in one set of exams (required: Mathematics at A*) IB: from 38 points with 766 at HL to 34 points with 765 at HL
About this course
BSc (Hons) in Applied Mathematics, a mathematics degree centred on analytical techniques and quantitative methods. Core topics include Data Analysis, Statistics, Mathematical Modelling, and Artificial Intelligence & Machine Learning. Students can transition between the BSc and MMath programmes until the beginning of the fourth year. The first year covers core foundations through Introduction to Mathematics at University, Introduction to Mathematical Analysis, Linear Algebra 1, and Introduction to Data Science. The second year progresses with Linear Algebra 2, Elementary Probability and Statistics, Further Analysis and Several Variable Calculus, and Modelling and Computing. Year 3 introduces compulsory and optional areas including Statistics, Topology, Algebra, Analysis, Operational Research, Differential Equations, Numerical Analysis, Probability and Measure Theory, Financial Mathematics, Introduction to Number Theory, and Statistical Computing. The final year allows specialisation across applied mathematics, statistics, operational research, financial mathematics, mathematical biology, mathematical education, Stochastic Modelling, Mathematical Physics, Machine Learning in Python, and Applied Dynamical Systems.
Modules
- Introduction to Mathematics at University
- Introduction to Mathematical Analysis
- Linear Algebra 1
- Introduction to Data Science: you will learn to collect and explore data, before using models and predictions to make rigorous conclusions
- Fundamentals of Algebra and Calculus: an online, introductory course that provides extra preparation in key topics from advanced high school level mathematics and further supports your transition to university
- Linear Algebra 2
- Elementary Probability and Statistics
- Further Analysis and Several Variable Calculus
- Modelling and Computing
- Statistics
- Topology
- Algebra
- Analysis
- Operational Research
- Differential Equations
- Numerical Analysis
- Probability and Measure Theory
- Financial Mathematics
- Introduction to Number Theory
- Statistical Computing
- applied mathematics
- statistics
- operational research
- financial mathematics
- mathematical biology
- mathematical education
- Stochastic Modelling
- Mathematical Physics
- Machine Learning in Python
- Applied Dynamical Systems