Overview

Rapid advances in big data, predictive analytics and AI technologies have created genuine demand for people who can turn complex, fast-growing datasets into meaningful insight. The BSc (Hons) Data Science at the University of Aberdeen builds essential skills in programming, statistics, software engineering and data curation, before layering on advanced techniques in artificial intelligence, machine learning, deep learning, distributed systems and cybersecurity. The course goes beyond classical software engineering and statistics to teach students how to apply logical thinking, machine learning and computer algorithms to problems spanning many academic disciplines and industry sectors, with particular focus on AI systems and knowledge technologies. Students also build teamwork, leadership and entrepreneurship skills, and can gain hands-on experience through the Aberdeen Software Factory, a student-run software house working on real projects for external clients. The university's strong industry ties, including with organisations such as Amazon and CGI, bring case studies directly into lectures and seminars, while membership of the Turing University Network connects teaching to cutting-edge national research in data science and AI. The course suits students genuinely excited by developments in big data and AI who want technical depth across analysis, modelling and engineering. It particularly suits those aiming for careers as data scientists, data engineers or machine learning specialists across sectors from energy to healthcare.

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What You'll Learn

• Programming fundamentals, alongside calculus and algebra as mathematical foundations for data science

• Object-oriented programming, data structures and basic software engineering techniques

• Databases and data management, including spatial data and data warehousing

• Probability theory and statistical methods for summarising and interpreting data

• Algorithms and data structures, covering efficiency, computational complexity and implementation

• Software engineering practices, including team-based development of industrial-strength systems

• Artificial intelligence fundamentals, distributed systems and security

• Natural language processing and a substantial final-year individual research project

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Learning Outcomes

By the end of the course, students will be able to apply programming, statistical and software engineering skills to design and build systems that extract meaningful insight from complex data. They will be equipped to use algorithms, machine learning and computational thinking to solve problems across a wide range of academic disciplines and industry sectors, with particular strength in AI systems and knowledge technologies. Through team-based software development and an individual research project, students will develop the practical, collaborative and research skills needed to explore real computing system behaviour and report on their findings rigorously. Graduates will leave with strong technical, analytical and entrepreneurial skills, well prepared for careers such as data scientist, data architect, business intelligence analyst or data mining engineer across sectors including energy, finance, health and government.