University of Hull

What you'll study

This online MSc covers the theoretical foundations and practical application of artificial intelligence and machine learning. The programme combines modules in statistical and machine learning, deep learning, natural language processing, computer vision, and AI ethics with training in software engineering for AI systems and data management for large-scale applications.

• Core techniques: supervised and unsupervised learning, neural networks, reinforcement learning, model evaluation and optimisation.
• Applied areas: natural language processing, computer vision, time-series and sensor data, and applied data mining.
• Systems and deployment: engineering for scalable AI, cloud-based model deployment, MLOps concepts and reproducible research practices.
• Professional and ethical context: AI safety, fairness, privacy, legal and societal implications of AI applications.
• Research methods and project: research skills, literature review, and a substantial independent project or dissertation that applies AI methods to a real-world problem or dataset.

Delivery is online through a blend of recorded lectures, live seminars, practical programming labs (typically using Python and common libraries such as TensorFlow/PyTorch and scikit-learn), assessed coursework and a final research or industry-facing project. The programme is designed so that students can build a portfolio of code, notebooks and project reports to demonstrate skills to employers.

Entry requirements

Applicants are normally expected to hold a UK honours degree (minimum lower second class, 2:2) or an international equivalent in Computer Science, Engineering, Mathematics, Statistics, Data Science or a closely related discipline. Applicants with a non‑numerical degree plus relevant professional experience in software development, data analysis or a technical role may also be considered.

Typical academic background should include programming experience (Python is commonly used) and familiarity with core mathematical concepts such as linear algebra, probability and calculus. Where gaps exist, students are expected to undertake preparatory study or bridging modules prior to, or early in, the programme.

English language proficiency is required for applicants whose first language is not English; usual acceptable evidence includes recognised qualifications at an appropriate level (for example an overall score equivalent to IELTS 6.5 with no lower than 6.0 in any component), or other approved tests or exemptions.

Career prospects

Graduates of the MSc Artificial Intelligence progress into a range of technical and research roles across sectors. Typical job titles include:

• Machine Learning Engineer
• Data Scientist / Senior Data Analyst
• AI Engineer or Applied AI Specialist
• Computer Vision or NLP Engineer
• Research Assistant or PhD candidate in AI-related fields
• Technical consultant or product specialist working with AI-enabled systems

Alumni work in industries such as healthcare, finance, retail, manufacturing, government and technology start-ups. The programme emphasises transferable skills in problem specification, model development, data handling and production deployment, making graduates attractive to employers seeking to operationalise AI solutions.

Why study at University of Hull

Studying the MSc AI at the University of Hull online gives you flexibility to combine study with work or family commitments while following a course designed by academic staff with research and industry experience in data analytics and machine learning. The online format includes structured tutor support, regular live sessions and access to digital learning resources and programming labs.

The University provides dedicated student support services, including careers advice, dissertation supervision and technical help for remote learners. The programme encourages applied projects that can be aligned with employer needs or research interests, helping you build a practical portfolio. Hull’s emphasis on employability and real-world application helps graduates move into professional AI and data roles or continue to doctoral research.