Artificial Intelligence (online) MSc

Course overview

Master the skills shaping the future and fast track your career with a transformative education in the principles and practice of artificial intelligence.

This programme has been refreshed for 2026 in response to the continual pace of change and innovation in AI.

Designed and delivered by computer scientists, this innovative and contemporary online Masters in Artificial Intelligence is tailored for professionals who recognise AI’s growing impact on every sector. You’ll gain the knowledge and practical skills to influence organisational strategy, drive efficiencies and shape future business processes.

Focusing purely on AI, the programme covers an extensive range of AI and Machine Learning tools and techniques. You’ll apply your learning directly to real-world projects, equipping you to excel in your chosen sector and adapt to the rapidly evolving tech landscape.

Specialist modules including Machine Learning, Neural Networks & Deep Learning, Reinforcement Learning and Modern Learning Paradigms as well as Deep Learning for Computer Vision have been developed in response to industry demand, and the pace of AI change ensuring you gain high-value, in-demand skills.

With businesses increasingly needing to understand and leverage AI, our modern technology-driven curriculum prepares you to apply advanced analytical and problem-solving skills to design, implement, and evaluate intelligent systems that address complex and uncertain real-world challenges and confidently advise on the adoption of emerging technologies.

If you see the transformative potential of AI in your industry, this online Masters in Artificial Intelligence will equip you with the advanced knowledge and practical skills to accelerate your career.

It is ideal if you want to:

• Reskill for a career as an AI developer.
• Upskill to design, implement and manage AI solutions in your organisation.
• Develop your academic understanding of AI through advanced postgraduate study.

With a curriculum covering machine learning, deep learning, the ethics of AI and neural networks, you’ll graduate ready to make informed, strategic decisions that shape the future of your sector.

Course highlights

Academic and research excellence

• Ranked among the top 100 universities in the world and top 13 in the UK (QS World University Rankings, 2026).
• At the School of Computing, 99% of the submitted computing research was rated "world-leading" or "internationally excellent" (REF 2021).

Exclusive Partnerships

• Alan Turing Institute – We are one of a select group of UK institutions partnering with the national institute for data science and AI, tackling real-world scientific and societal challenges at the forefront of innovation.
• Leeds Institute for Data Analytics (LIDA) – A hub connecting world-class research with business, government, and third-sector partners to address health, social, and environmental challenges using data-driven insights.

Course details and modules

Our Artificial Intelligence MSc begins with a two-week online induction designed to prepare you for online learning at the University of Leeds. It will introduce the study skills you will need to successfully complete your degree.

Delivered online, the artificial intelligence course offers a flexible schedule of modules which are structured to be accessible to working professionals. There are nine individual 15-credit taught modules, and you will typically spend eight weeks studying each module, plus a 45-credit project module over 24 weeks.

The modules cover a variety of subject areas such as machine learning, deep learning, and programming to teach you the technical elements of AI. The Artificial Intelligence research project enables you to apply the principles, techniques and knowledge developed across the programme to develop AI solutions to the real world, encouraging you to explore, analyse, and innovate upon existing critical theory and practice.

You can take the course at your own pace and adapt your studies to fit around your work and life commitments. To give you flexibility, it is possible to pause your studies and take them up again at a later point. This means you can choose to complete the Masters in Artificial Intelligence in a minimum of two years or up to a maximum of four years.

Please note: You might have to take a study break to complete the artificial intelligence online course depending on when the selected module is next running.

Course structure

The list shown below represents typical modules/components studied and may change from time to time. Read more in our terms and conditions.

For more information and a full list of typical modules available on this course, please read Artificial Intelligence (online) MSc in the course catalogue

We have refreshed several modules on the programme in response to the continued pace of change and innovation in AI. We see these updates as continuous improvement to our degree, ensuring it remains current, relevant, and aligned with evolving industry and research developments.

Please note: You must finish each carousel before you can move on to the next one.

Foundation carousel

Programming for Data Science (15 credits)
You’ll be introduced to core programming concepts and computational thinking for data-driven problem solving. You will learn to design, implement, and debug programs for data acquisition, analysis, and visualisation using Python, supporting those new to programming and stretching those with prior experience.

Ethics of Artificial Intelligence (15 credits)
Grasp the analytical and conceptual tools needed to identify and evaluate the ethical, legal, and societal implications of AI systems. You will explore and comprehend key ethical issues and areas of concern in the development and deployment of AI systems, including issues related to fairness, bias, transparency, privacy, surveillance, and accountability.

Mathematical Foundations of Artificial Intelligence (15 credits)
Develop the core mathematical foundations underpinning artificial intelligence (AI) and machine learning. You will be introduced to key concepts from linear algebra, vector calculus, probability, and analytical geometry that support the quantitative reasoning essential to AI.

Development carousel 1

Machine Learning (15 credits)
Take an introduction to the fundamental principles and techniques of classical machine learning, with an emphasis on statistical approaches to learning from data. Explore how models capture patterns, make predictions, and generalise through both statistical and non-statistical methods, including regression, classification, clustering, and ensemble techniques.

Machine Learning Operations (15 credits)
Delve into the principles and practices of machine learning operations (MLOps), focusing on how machine learning models are developed, deployed, and managed in production-oriented settings. Cover the end-to-end lifecycle of artificial intelligence (AI) systems, including workflow automation, version control, testing, and monitoring, alongside computational aspects such as GPU acceleration and high-performance computing for efficient training and experimentation.

Neural Networks and Deep Learning (15 credits)
Understand the principles and practice of artificial neural networks and deep learning as a foundation for modern artificial intelligence (AI). You will explore how layered representations enable machines to learn from complex data, including images, sequential data such as text and time series, and relational data such as graphs.

Development carousel 2

Deep Learning for Computer Vision (15 credits)
Explore deep learning techniques for computer vision, focusing on how neural networks interpret, represent, and generate visual information. You will examine architectures and algorithms that enable tasks such as image classification, object detection, segmentation, and visual synthesis.

Deep Learning for Natural Language Processing (15 credits)
Investigate how deep learning methods enable machines to process, understand, and generate human language. You will examine how modern language models are built and trained, how they align with human intent, and how their memory and retrieval mechanisms can improve factual grounding and reduce hallucination.

Reinforcement Learning and Modern Learning Paradigms (15 credits)
Take an introduction to the principles and methods of reinforcement learning, focusing on how intelligent agents learn to make sequences of decisions through interaction with their environment. You will examine how experience, feedback, and exploration guide learning and adaptation over time.

Advanced carousel

Artificial Intelligence Project (45 credits)
Produce an independent and substantial project in artificial intelligence, drawing on the knowledge and skills developed across the programme. You will pursue either a research-focused or applied project under academic supervision, culminating in a comprehensive project report written in the style of a scientific paper. You will need to demonstrate technical competence, analytical depth, and the ability to conduct and communicate sustained work in AI.

Learning and teaching

Join our powerful learning network

Your learning will be delivered online via our virtual learning environment, Minerva. Each week you will study through live face-to-face sessions with our world-class academics.

We recognise that professionals have busy lives, so with a 100% online delivery mode, students can manage their learning around their busy personal and full-time employment, without the need to disrupt their life. You will also be given access to premium-quality study videos, library resources and the industry’s top electronic journals for independent study.

Our artificial intelligence online course is designed to ensure professionals living and working across the world together can share experiences and knowledge with each other. Collaborate and learn from like-minded professionals during regular interactive activities, including live seminars, virtual discussions, and group projects. This allows you to develop a range of transferable skills and grow confidence and strength in character studying within a growing community of virtual learners.

Introducing Minerva

Social learning is at the heart of your learning experience, with interactive and collaborative activities embedded into every module of this course. It’s what brings your online learning experience to life through:

• synchronous and asynchronous video lessons
• interactive surveys, tests, polls and exercises
• weekly live tutorials with classmates and academics
• group projects and discussion boards
• individual access to reading and study resources
• flexible study sessions to allow you to join at any time that suits you.

Minerva can be accessed from anywhere with an internet connection and is mobile friendly, so you can study on the go around your existing work and life commitments. You can also benefit from downloadable PDFs on course content for offline reading when required.

We recommend a high-speed broadband internet connection with a minimum speed of 1.5 Mbps. You will need regular access to a desktop computer, tablet or laptop, with a webcam. You will also need the ability to view PDF documents and work in Microsoft Office (software provided).

On this course, you’ll be taught by our expert academics, from lecturers through to professors. You may also be taught by industry professionals with years of experience, as well as trained postgraduate researchers, connecting you to some of the brightest minds on campus.

Assessment

Assessment methods will emphasise not just knowledge, but essential skills development too. The Artificial Intelligence MSc will typically be assessed through:

• mini project reports
• group discussions and assignments
• live and/or pre-recorded presentations
• practical exercises based on real-world scenarios
• essays
• literature reviews
• multiple choice exams for formative learning feedback (no more than 5% of assessment).

Applying

Entry requirements

Standard Entry

You must have a 2.1 or above honours degree in a mathematical, computational, engineering or other numerate discipline, including but not limited to:

• Computer Science, Data Science, AI
• Mathematics, Statistics, Physics
• Engineering
• Economics or quantitative Social Sciences

Your degree should include at least one numerate or programming-related module.

Professional Entry

You are eligible through this route if you meet at least one of the following:

• A 2.2 or above in a non-numerate degree plus 1 year of relevant professional experience
• A third-class degree in any discipline plus 2 years of relevant professional experience
• At least 3 years of relevant professional experience in a technical, analytical or digital role

Relevant experience includes, but not limited to data analysis, coding, automation, software testing, reporting, digital transformation, or any role involving analytical or technical problem-solving.

Additional Information

• A short numeracy or programming readiness task may be required
• Professional certifications in data, cloud, coding or AI strengthen your application

We accept a range of international equivalent qualifications. For information please contact our Enrolment Advisors at studentenquiries.online@leeds.ac.uk.

Proof of your English Language Proficiency

Proficiency in English language is essential to study at the University of Leeds. Applicants will need to have GCSE English language at grade C or above, or an appropriate equivalent English language qualification. You will need either:

Alternative English Language Qualification
A degree taught in English from a recognised institution, lasting at least two years at the undergraduate level or one year at the Masters level, which can be evidenced by transcripts and/or certificates.

In exceptional circumstances, applicants can provide alternative proof of English language proficiency rather than a standard English test. This will be assessed on a case-by-case basis. You should discuss the criteria with your Enrolment Advisor to see if this can be considered.

English language requirements

IELTS 6.5 overall, with no less than 6.0 in any component. For other English qualifications, read English language equivalent qualifications.

How to apply

The ‘Apply’ button at the top of this page takes you to the University's online application system, where you can start your application for this course. Alternatively, you can request further information by ‘registering your interest’.

Identification

The Digital Education Service requires all applicants to provide proof of their identity at the point of application. Accepted forms of ID are:

• Passport photo page, or
• Driving licence, or
• National identity card.

Deadlines

The deadline for applications to join each intake are outlined below:

• May 26 start: application deadline is 21 April 2026
• July 26 start: application deadline is 16 June 2026
• September 26 start: application deadline is 18 August 2026

All suitably qualified candidates will be interviewed by telephone or online as part of the selection process.

Applicants for Digital Education Service programmes should contact their Enrolment Advisor to find out more about the course, how to start the online application process and if applicants wish to change their start date after submitting an application.

Email studentenquiries.online@leeds.ac.uk.

Admissions policy

University of Leeds Admissions Policy 2026

Contact us

Enrolment Advisor team

Email: studentenquiries.online@leeds.ac.uk
Telephone: +44 (0)113 868 6129

Fees

UK: £15,000 (Total)

International: £15,000 (Total)

Additional cost information

There may be additional costs related to your course or programme of study, or related to being a student at the University of Leeds. Read more on our living costs and budgeting page.

Scholarships and financial support

If you have the talent and drive, we want you to be able to study with us, whatever your financial circumstances. There may be help for students in the form of loans and non-repayable grants from the University and from the government.  Find out more at Masters funding overview.

Scholarships are also available to help fund your Masters. Find out more and check your eligibility below: 

• Scholarships for International students 
• Scholarships and funding for UK students
• Your subject area may also offer scholarships

Career opportunities

The University of Leeds Careers Service offers extensive online resources to help you maximise your studies and achieve your career goals:

• One-to-one support from a careers advisor via phone or virtual meetings
• Online career workshops, webinars and career resources
• A job database and online employer events
• LinkedIn Learning platform access
• CV writing guidance and job application support
• Interview coaching and practice sessions.

Find out more about careers support.