Artificial Intelligence (online) PGCert

Course overview

Advance your career with the Online PGCert in Artificial Intelligence: Gain future-ready skills fast.

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

The Online Artificial Intelligence Postgraduate Certificate is both a recognised postgraduate qualification and a stepping stone to the full MSc in AI. Designed and delivered by computer scientists, it is ideal for professionals who want to develop the analytical fluency and computational confidence required to engage deeply with AI technologies without committing to a full Masters right away.

This Level 7 qualification provides a solid foundation of AI theory, tools, and techniques, equipping you with skills that employers value. You’ll study three compulsory modules and one optional module from the MSc programme, giving you the flexibility to focus on areas most relevant to your career.

Your learning will help you apply AI to real-world problems, inform organisational strategy and evaluate the risks and opportunities of emerging technologies making you a valuable asset in any forward-thinking organisation.

Who’s this course for?

If you want to quickly develop specialist AI skills for the future of your industry but can’t commit to a full Masters degree, the online Artificial Intelligence Postgraduate Certificate offers a focused, career-enhancing route to gain in-demand expertise.

This course is for professionals across diverse sectors who want to stay ahead in a rapidly changing tech landscape.
It is ideal if you want to:

• Reskill to transition into AI development or integration roles
• Upskill to design, manage and plan AI solutions within your current organisation
• Lay the foundation for higher-level study, progressing towards an MSc in Artificial Intelligence.

Through targeted modules, you’ll gain practical knowledge of AI tools and techniques, enabling you to apply your learning immediately and prepare for future opportunities.

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 Computer Science, 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 Postgraduate Certificate 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.

The four modules provide enough AI coverage to speak directly to the skills that employers are seeking within the AI development sector.

After completing the three compulsory modules, you’ll be able to select one more module from the optional list that most interest you.

Please note: The minimum programme duration is 8 months. Depending on when you start the programme it may not be possible to complete the programme in 8 months. You might have to take a study break to complete the 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) PGCert in the course catalogue

We’ve 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.

The first three modules are compulsory: Programming for Data Science, Mathematical Foundations of AI and Ethics of AI, plus one choice from Machine Learning Operations & Optimisation, Machine Learning or Neural Networks & Deep Learning.

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 learn to 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 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

(Choose 1 of these 3 modules after completing the Foundation carousel)

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.

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 in a mixture of structured and open-ended learning techniques.

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 online learning 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. They will typically include:

• 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. 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.

For more details, contact our Enrolment Advisors at onlineadmissions@leeds.ac.uk

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: £5,800 (Total)

International: £5,800 (Total)

The fee is composed of:

• four taught modules (15 credits each): £1,450 per module

You will have the option to pay your fees on a module-by-module basis*. In this case your fee will be broken down into:

• four equal payments of £1,450

*If your fees are being paid directly to the University by your employer or sponsor you will not be able to pay on a module-by-module basis.

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 engages in industry collaboration with domestic and worldwide partners. Our industry links help us to build a curriculum designed specifically to meet growing market demands.

An additional resource for you is the virtual learning environment (Minerva) which provides access to a range of resources including study skills support, interactive and collaborative communication tools, and reflective personal and professional development opportunities.

Careers support

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.

The Careers Service also connects students seeking to work in a specific region, and offers professional development through alumni network, online support and employer partnerships.

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