Coventry University

What you'll study

This programme blends core data science topics with computational intelligence approaches to deliver both theoretical understanding and practical skills. Typical core modules cover foundations of data science and statistics, machine learning and deep learning, big data technologies and data engineering, plus specialised computational intelligence topics such as evolutionary computation, fuzzy logic and hybrid intelligent systems.

• Foundations of Data Science and Statistical Methods – probability, inference, exploratory data analysis and feature engineering.
• Machine Learning and Deep Learning – supervised and unsupervised methods, neural networks, convolutional and recurrent architectures, and model evaluation.
• Computational Intelligence – evolutionary algorithms, swarm intelligence, fuzzy systems and hybrid approaches for optimisation and adaptive systems.
• Big Data Technologies and Data Engineering – distributed processing, data pipelines, cloud platforms, and scalable storage solutions.
• Data Visualisation and Communication – techniques for presenting results to technical and non-technical stakeholders, dashboarding and storytelling with data.
• Responsible AI, Ethics and Governance – fairness, transparency, privacy and legal considerations in data-driven systems.
• Research Project or Industry Consultancy Project – an extended independent project where you apply methods to a real dataset or industrial problem, culminating in a dissertation and presentation.

Teaching methods typically include lectures, practical labs, group projects, and guest sessions with industry practitioners. Assessment is by a mixture of coursework, programming assignments, project reports and the final dissertation or consultancy project.

Entry requirements

Applicants are normally expected to have a recognised undergraduate degree in a relevant subject such as computer science, mathematics, statistics, engineering, or a closely related discipline. Applicants with other degrees backed by relevant professional experience or strong quantitative skills may also be considered.

International applicants will need an English language qualification equivalent to UK requirements for postgraduate study. Where appropriate, applicants may be asked to provide a portfolio of relevant work or to attend an interview.

Career prospects

Graduates of this MSc are prepared for technical roles that combine data science and AI. Typical job titles include data scientist, machine learning engineer, AI engineer, data engineer, analytics consultant and research assistant. The programme’s emphasis on scalable data systems and computational intelligence also equips graduates for roles in sectors such as finance, healthcare, automotive and manufacturing, telecommunications and public sector analytics.

Alumni may also progress to research degrees (MPhil/PhD) or specialist professional pathways in applied AI, Big Data platforms and algorithmic optimisation.

Why study at Coventry University

Coventry University emphasises applied learning and industry relevance, with course design focused on hands‑on experience and project work with real datasets. Students benefit from modern computing facilities and lab environments, opportunities for collaboration with local and national industry partners, and teaching from staff with postgraduate research and industrial backgrounds.

The university supports career development through employer engagement, placement and project opportunities, and enterprise services to help you build a professional portfolio. The programme’s balance of theoretical foundations, practical engineering and an independent project makes it suitable for those aiming to enter or advance in data-driven and AI-focused careers.