BSc Economics and Mathematics with a Year in Business
Royal Holloway, University of London
Entry requirements
A level: AAB-BBB (Required subjects: A-level Mathematics at grade A We require English Language and Mathematics GCSE at grade 4/C) IB: 6,6,5 - 5,5,5 at Higher Level or 34-30 points overall including 6 in Maths at Higher Level
About this course
BSc in Mathematics and Economics, combining quantitative methods with economic theory. Core topics include Statistics, Mathematical Modelling, Data Analysis, Programming, Policy Analysis, and Artificial Intelligence & Machine Learning. An optional year in industry is available and the placement mark counts towards the final degree classification. A Machine Learning and Data Mining module covers neural networks, ensemble methods and unsupervised learning.
Modules
- Principles of Economics
- Applied Economics and Policy
- Academic Integrity
- Statistical Methods 1
- Calculus
- Calculus II
- Introduction to Pure Mathematics
- Linear Algebra I
- Microeconomics
- Macroeconomics
- Statistical Methods 2
- Probability Theory
- Financial Markets and Institutions
- Industrial Growth and Competition
- Personnel Economics
- Introduction to Economic Growth
- Vector Calculus
- Ordinary Differential Equations and Fourier Analysis
- Linear Algebra II
- Ring Theory
- Group Theory
- Further Linear Algebra and Modules
- Complex Analysis
- Year in Business
- Machine Learning and Data Mining
- Industrial Economics 1
- Financial Economics 1
- Financial Economics 2
- Advanced Econometrics I
- Advanced Econometrics II
- Understanding Financial Crises
- Environmental Economics
- Behavioural Economics
- Monetary Economics
- Topics in Game Theory
- Advanced Economic Theory
- Financial Econometrics with Data Science
- Labour Economics
- Philosophy of Economics
- Public Economics
- Topics in Economic History
- Data Presentation and Visualisation
- Advanced Topics in Game Theory
- Economics of Inequality
- Dissertation in Economics
- Mathematics Project
- Number Theory
- Complexity Theory
- Quantum Theory 1
- Non-Linear Dynamic Systems
- Inference
- Time Series Analysis
- Channels
- Mathematics of Financial Markets
- Combinatorics
- Cipher Systems
- Electromagnetism
- Applications of Field Theory
- Mathematics in the Classroom
- Computational Number Theory
- Principles of Algorithm Design
- Dynamics of Real Fluids
- Quantum Theory 2
- Markov Chains and Applications
- Quantum Information and Coding
- Financial Mathematics I
- Financial Mathematics II
- Error Correcting Codes
- Cryptography
- Topology
- Introduction to Optimisation