Artificial Intelligence* (MSc)

About the Course

*Subject to validation

At a time when artificial intelligence is reshaping industries from drug discovery to autonomous transport, the MSc Artificial Intelligence at Liverpool Hope University invites you to move beyond simply using AI to truly understanding, building and questioning it. This programme is designed for ambitious graduates and professionals who want to combine mathematical rigour with real-world impact, whether you’re a recent graduate in computing or a professional seeking to pivot into the fastest-growing sector in the global economy.

What sets this course apart is that you won't just learn how algorithms work, but you'll derive them, implement them in Python and apply them to messy, real-world data. From mastering the mathematical foundations behind machine learning to exploring cutting-edge areas like spatial AI, robotics and ethical AI systems, the curriculum covers the full lifecycle of a modern AI system from mathematical foundations through to deployment.

A defining feature of the programme is its strong emphasis on responsibility and relevance. With dedicated training in AI ethics, safety and governance, you’ll engage directly with pressing global challenges such as bias, transparency and regulation. Opportunities to interact with industry experts and undertake independent research ensure your learning remains both current and career-focused.

If you’re motivated to shape the future of intelligent technologies, rather than just follow it, this MSc offers the tools, depth and confidence to do exactly that. 

Curriculum Overview

The MSc Artificial Intelligence at Liverpool Hope University is delivered by active researchers working across machine learning, cryptography, computer vision, robotics and privacy-enhancing technologies.  This is so that teaching draws directly on current research rather than relying solely on textbooks.

One main strength of the programme is the integration of research into the classroom. Students are exposed not only to established techniques but also to emerging ideas and open research questions, often drawn directly from staff projects and industry collaborations. This means students encounter open problems and unsettled questions, not just established techniques. For example, in Machine Learning Algorithms, students don't just implement models but evaluate competing approaches, design experiments, and critically interpret results.

The University supports this learning with a range of modern facilities and applied teaching approaches. Dedicated computing labs equipped with GPU resources, PyTorch and cloud platforms, with practical environments for robotics and spatial AI, support applied project work from week one. Small-group teaching, interactive labs, and project-based assessments ensure close academic support and meaningful engagement.

Modules

The MSc Artificial Intelligence at Liverpool Hope University is carefully structured to take students from core foundations to independent advanced work, from building core technical foundations to developing advanced and independent expertise. Throughout the programme, students grow not only as skilled AI practitioners but also as researchers equipped to work responsibly and independently.

The programme begins with Foundations in AI, where students establish the mathematical foundations of the field. Topics such as linear algebra, probability, optimisation, and information theory are taught through practical machine learning examples, so that every concept is tied to a working implementation. This grounding is essential for Machine Learning Algorithms, where students engage deeply with classical models and modern approaches, including deep learning and reinforcement learning. Here, students build fluency in Python while learning to think algorithmically about open-ended problems.

In parallel, Applied Data Skills for AI introduces the full data pipeline, equipping students with the ability to source, clean, analyse, and visualise real-world data. This prepares students for the reality that production data is rarely clean or complete. With this, Research Methods cultivates academic and professional skills such as critical evaluation, ethical reasoning and effective communication, preparing students to design and defend rigorous research.

Students can then tailor their learning through optional modules, allowing for specialisation in areas aligned with their interests and career goals. Whether exploring large-scale analytics in Big Data, building connected systems in Internet of Things (IoT), strengthening theoretical understanding in Theoretical Computer Science or deepening mathematical insight in Numerical Methods, students gain breadth and depth. The inclusion of Spatial AI later connects the field with the physical world through robotics, vision systems and geospatial reasoning.

A defining feature of the curriculum is its emphasis on responsible innovation. The AI Ethics and Safety module ensures students are equipped to address real-world challenges such as bias, transparency and regulatory compliance - key concerns in today’s AI landscape.

The programme culminates in a Dissertation, where students undertake an independent research study or applied project, for example building a bias-detection pipeline, developing a reinforcement learning agent or evaluating federated learning protocols. This is an opportunity to integrate knowledge, demonstrate technical depth and analytical judgement and explore a topic of personal or professional significance, often with links to industry or real-world applications.

By the end of the course, students will have developed advanced technical expertise and an ability to tackle complex problems, clearly communicate findings and work responsibly within a rapidly changing field. 

Entry Requirements

Normally a minimum of a Second-Class Honours degree in a relevant discipline awarded by a UK university, or an equivalent higher education qualification is required.

International Entry Requirements

Possess a degree from an overseas institution that is judged by the Registrar or Nominee to be equivalent to a second class honours degree from a UK University.

For students whose first language is not English there is a language requirement of IELTS 6.5 overall with 6 minimum of all components. In addition to this, we also accept a wide range of International Qualifications, for more information please visit our English Language Requirements page.

For additional information about country specific entry requirements visit the your country pages. 

*Part time study is not available for Non-UK applicants

Teaching and Research

Choosing to study at Liverpool Hope University means joining a well-established academic community that values scholarly engagement and intellectual development. With a strong emphasis on rigorous teaching and small-group learning, you will benefit from sustained interaction with lecturers and structured academic guidance throughout your MSc journey.

Located in the vibrant and culturally rich Liverpool, the University offers more than just a degree. The city has a growing tech and digital sector, with start-ups and established companies offering networking and employment opportunities on your doorstep. It's also one of the most affordable cities for postgraduate study in the UK.

Liverpool Hope consistently scores well for student satisfaction and teaching quality. Modern facilities, dedicated computing resources and access to emerging technologies support your learning.  Scholarships and funding opportunities also help make postgraduate study more accessible. Together, this creates an environment where you can thrive academically, professionally and personally.

Home Fees

Tuition fees for Home students for 2027/28 are £10,500.

International Tuition Fees

Tuition fees for Non-UK International students for 2027/28 are £17,750

Funding your studies

If you're a UK national, or have settled status in the UK, you may be eligible to apply for a Postgraduate Loan to help with course fees and living costs. Liverpool hope University also offers a number of scholarships to help fund your Postgraduate Studies. Learn more about paying for your studies.

If you are an international student, visit our international scholarships pages.

Careers

Graduates of the MSc Artificial Intelligence at Liverpool Hope University are well positioned to enter high-demand roles across established and emerging sectors. The programme prepares students for careers such as AI engineer, machine learning specialist, data scientist, robotics developer and AI consultant, as well as progression to doctoral research.

Industry engagement runs throughout the programme, with students engaging with external experts through guest lectures, case studies and project work. Practical skills in Python, cloud deployment and data pipeline development ensure graduates can contribute from day one. Opportunities to align dissertation projects with industry challenges further strengthen employability and professional networks.

Graduates may find opportunities across sectors including healthcare, finance, logistics, environmental monitoring and technology start-ups - areas where AI is driving rapid transformation. The programme also supports the development of transferable skills like problem-solving, communication and ethical decision-making, which are highly valued by employers.

With a strong foundation in theory and practice, graduates are equipped not only to enter the AI workforce but to adapt and lead as the field evolves.