Overview

Data now drives decisions across banking, government and business alike, and combining rigorous economic theory with modern computational skill has become genuinely valuable for tackling real-world financial and social questions. The BSc (Econ) Economics and Data Science at Royal Holloway, University of London blends core economic principles with applied data science, teaching Python programming, machine learning and AI tools alongside traditional economic modelling. The course follows the CORE approach to teaching economic principles, encouraging students to formulate real problems, build theory to address them, and test that theory against data. Students benefit from maths support and Data Lab drop-ins from their very first term, alongside a personal academic advisor and short employability modules built into every year of study. The department combines strong research credentials with genuine industry links, giving students exposure to academics actively shaping the future of both economics and data science. The course suits students who want a flexible, technically grounded route into economics, developing a portfolio of practical, work-ready skills across coding, statistical analysis and communication. It particularly suits those aiming for analytically demanding careers in banking, technology, consulting or government.

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What You'll Learn

• Core economic theory, including macroeconomics, microeconomics and applied economics and policy

• Mathematical tools for economics, including linear algebra, optimisation and differentiation

• Data skills using the R statistical software package, including data collection, analysis and clear communication

• Programming using Python for data science applications within economic and financial contexts

• Economic modelling and econometrics, including regression-based techniques for causal inference and forecasting

• Advanced optional topics such as behavioural economics, game theory, corporate finance and labour economics

• Structured employability training, including CV building, interview practice and networking with industry professionals

• Independent research skills, with the option to complete an extended essay in the final year

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Learning Outcomes

By the end of the course, students will be able to apply core economic theory alongside applied data science techniques to analyse and interpret real-world economic and financial issues. They will be equipped to use Python and R to collect, manipulate and present data, applying econometric methods to draw causal inferences and produce forecasts. Through hands-on lab work and increasingly advanced coursework, students will develop the ability to formulate research questions, test them against real data, and communicate findings both visually and narratively. Graduates will leave with strong numeracy, computing and analytical skills, alongside CIMA exemptions and structured employability training, well prepared for careers in banking, technology, consulting, government or further postgraduate research.