Overview

Turning raw data into meaningful insight now shapes decisions across nearly every industry, and doing it well demands genuine fluency across mathematics, computing and engineering. The BSc (Hons) Data Science at the University of York is jointly delivered by the Department of Computer Science and the Department of Mathematics, teaching students to analyse, manage and interpret data through programming, machine learning and statistical techniques. Students complete a substantial research project, gaining hands-on experience of critical analysis and collaborative, industry-facing problem-solving. The course suits students who want a genuinely interdisciplinary route into data science, with the option to add a placement year for real workplace experience.

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What You'll Learn

• Core programming, alongside foundational probability, statistics and calculus

• Object-oriented data structures, algorithms and an introduction to data science

• Operating systems, security, networking and software engineering principles

• Machine learning, optimisation and linear algebra

• Statistical inference and linear modelling techniques

• The governance and ethics of data science, alongside cloud-based data analysis

• A substantial research project in either computer science or mathematics

• Specialist final-year options such as deep learning, time series analysis or mathematical finance

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Learning Outcomes

By the end of the course, students will be able to apply computational, mathematical and statistical theory to solve real data science problems, drawing on strong skills in programming, software engineering and analytical reasoning. They will be equipped to critically evaluate the theoretical foundations of mathematics, statistics and computer science, using this understanding to mine and manage data in search of meaningful patterns. Through a substantial research project and specialist final-year options, students will develop the ability to communicate complex ideas clearly to a range of audiences and adapt to new tools, technologies and mathematical approaches. Graduates will leave able to apply their skills to real datasets from industrial partners in a safe, ethical and secure way, well prepared for a data-driven career.