Overview

Data now shapes decisions in nearly every field, from scientific research to commerce and public services, and the ability to interpret it has become a highly valued skill. Studying BSc (Hons) Data Science at Keele University introduces students to the methods used to collect, analyse and communicate information at scale. The course is designed and taught by active researchers, which keeps the content closely tied to current developments in artificial intelligence, machine learning and analytics. No previous programming experience is needed, because technical ability is built up gradually from first principles. Practical projects run throughout, including a research project linked to industry, while guest lectures and careers support bring a professional perspective into the learning. Teaching takes place in well-equipped computing labs offering industry-standard software, Windows and Linux systems, a high-performance computing cluster and JupyterHub access, alongside a dedicated cyber security lab. The course suits students who enjoy solving problems with real data, and graduates gain both strong technical competence and the confidence to apply it across a range of sectors.

What You'll Learn

Artificial intelligence and its practical applications

Machine learning methods and model development

Data analytics applied to complex, real-world datasets

Programming skills developed from the ground up

Data visualisation and storytelling for clear communication

High-performance computing and JupyterHub-based analysis

Industry-linked research project work

Professional development through guest lectures, careers support and an optional work placement

Learning Outcomes

By the end of the course, students will be able to write and use code with confidence, prepare and analyse complex datasets, and apply artificial intelligence and machine learning techniques to practical problems. They will understand how these methods operate at different scales, from individual analyses on standard systems to larger workloads run on high-performance computing resources. Students will learn to evaluate critically which analytical approaches suit a given question, and to apply them to real issues in science, business and society rather than treating them as abstract theory. They will also be able to present findings through effective visualisation and clear narrative, so that technical results can inform non-specialist audiences. Hands-on experience in the computing labs and through an industry-linked research project develops practical, workplace-ready skills, and an optional placement allows further professional experience. Project work also lets students focus on the areas that interest them most, whether that is AI, machine learning or analytics, and prepares them to continue into specialised roles or further study.