Advanced Artificial Intelligence MSc
Source: https://www.ncl.ac.uk/postgraduate/degrees/5449f/ Parent: https://www.ncl.ac.uk/postgraduate/degrees/
Postgraduate Study
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- Global Top 140 University
QS World University Rankings 2026
Top 145 for Engineering and Technology
QS World University Rankings by Subject 2025
Top 170 for Computing Science and Information Systems
QS World University Rankings by Subject 2025
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Global Top 140 University
QS World University Rankings 2026
Top 145 for Engineering and Technology
QS World University Rankings by Subject 2025
Top 170 for Computing Science and Information Systems
QS World University Rankings by Subject 2025
Overview
Gain the advanced skills to design, develop, and apply artificial intelligence technologies with our specialist technical degree. Drive innovation and solve complex challenges in the era of artificial intelligence (AI).
AI is transforming industries and reshaping how we solve complex problems.
AI creates intelligent systems that simulate human decision-making. This allows machines to:
- learn from data
- recognise patterns
- make predictions or decisions
These capabilities are driving innovation in areas such as natural language processing, computer vision, and autonomous systems.
Designed in collaboration with leading industry partners, this degree directly addresses the growing demand for skilled professionals with technical knowledge of AI.
The programme is guided by an Industrial Advisory Board, including representatives from:
- Meta
- JP Morgan
- PwC
The programme reflects latest industry trends, technologies, and employer expectations. You'll graduate ready to make an immediate impact in AI-focused roles.
You’ll gain the skills to design, develop, and deploy intelligent solutions that address real-world challenges. Topics covered include:
- statistics for AI
- machine learning
- deep learning
- natural language processing
- computer vision
You'll benefit from our substantial expertise in AI. We focus on a wide range of application areas, including:
- healthcare
- transport
- cybersecurity
- smart cities
- manufacturing
We are a hub of digital innovation. You'll benefit from our:
- leadership of the National Edge AI Hub, next-generation innovations via edge computing
- recognition as an Academic Centre of Excellence in Cyber Security, supported by the National Cyber Security Centre and the EPSRC
- direct link with the UK's National Innovation Centre for Data
- partnership with The Alan Turing Institute, the UK’s national institute for data science and AI
Quality and ranking
- Global Top 140 University - QS World University Rankings 2026
- Top 145 for Engineering and Technology - QS World University Rankings by Subject 2025
- Top 25 in the UK and Top 200 in the world for sustainable development – Times Higher Education Impact Rankings 2025
- 42% of our research is classified as 4* world-leading research – Research Excellence Framework 2021
- 65% increase in research power since 2014 – Research Excellence Framework 2021
- Global Top 145 University - Times Higher Education World University Rankings 2026
- Joint 64th in the world and 22nd in the UK for sustainability – QS World University Rankings: Sustainability 2026
- Top 170 for Computing Science and Information Systems - QS World University Rankings by Subject 2025
- Top 5 city for affordability in the UK – QS Best Student Cities 2026
- World Top 50 and UK Top 5 student city – QS Best Student Cities 2026
- 89th in the world - TIME Magazine: World’s Top Universities 2026
Professional accreditation and recognition
British Computer Society (BCS)
The course is accredited by the British Computer Society (BCS). The BCS is the chartered institute for IT. Studying a BCS-accredited degree provides the foundation for professional membership of the BCS on graduation and is the first step to becoming a chartered IT professional.
All professional accreditations are reviewed regularly by their professional body
Recognition of professional qualifications outside of the UK
If you’re studying an accredited degree and thinking about working in Europe after you graduate, the best place to find current information is the UK Government’s guidance on recognition of UK professional qualifications in EU member states. This official resource explains whether your profession is regulated in another country, what steps you need to take, and which organisation you should contact.
What stands out about my course is that it doesn't include written exams, which allows for a more practical and engaging approach to learning. The availability of term-time internship opportunities also provides valuable practical experience, as well as exposure to cutting-edge research and real-world applications of AI has inspired me to pursue research in the field.
What you'll learn
This Advanced Artificial Intelligence MSc has three phases.
Phase one
You'll develop a core knowledge and skillset in statistics and computer science
These modules are taught as an intensive block, meaning you'll be taught two modules simultaneously.
Phase two
Phase two consists of more advanced technical modules, as well as a group project.
We'll introduce the aspects that govern all areas of AI practice, including:
- professionalism
- legislation
- ethics
During the group project, you'll develop and evaluate an AI solution to a complex, real-world problem. You'll work in an industry organisation. They can be a regional, national or charitable organisation. You'll propose an AI project in that company, institute, or area of research.
Phase three
In your final phase, you'll work on an individual research project. It'll give you an opportunity to:
- develop your knowledge and skills
- work in a research or development team
You can develop your project:
- at the University under an academic supervisor
- by securing an industrial placement
- working with your current employer
You'll have one-to-one supervision from an experienced staff member. If needed, you'll also get supervision from industry partners.
Recent final year projects include:
- Personalized Music Generation and Recommendation for Art Works: Research Based on Multimodal Model
- Continual Learning in Deep Networks
- Detection of multiple documents from photos using computer vision / AI
Modules
You will study modules on this course. A module is a unit of a course with its own approved aims and outcomes and assessment methods.
Advanced Artificial Intelligence MSc modules
| Compulsory Modules | Credits |
|---|---|
| Data Visualization | 10 |
| Image Processing | 10 |
| Data Science in the Wild (Group Project) | 10 |
| Machine Learning with Project | 10 |
| Deep Learning | 10 |
| Project and Dissertation in Data Science | 80 |
| Advanced AI | 10 |
| Graduate Foundations of Statistics and Data Science | 30 |
| Optional Modules | Credits |
|---|---|
| Engineering for AI | 10 |
| Generative AI for Businesses | 10 |
How you'll learn
The School of Computing and School of Mathematics, Statistics and Physics deliver this course.
You'll be taught using a range of methods, including:
- seminars
- lectures
- practical classes
- group and individual project work
- guided independent reading
- self-directed learning
Depending on your modules, you'll be assessed through a combination of:
- Dissertation
- Oral presentation
- Poster
- Report
- Written examination
Additional assessment information
This degree uses both formative and summative assessments.
These assessments will:
- evaluate your overall understanding of the course content
- identify your strengths and areas for improvement
- encourage continuous learning and personal development
Formative assessments
Formative assessments are designed to provide ongoing feedback and support throughout the course. These assessments will help you identify your strengths and areas for improvement, fostering continuous development.
Examples of formative assessments include:
- Weekly quizzes: Short quizzes at the end of each module to test your understanding of the material.
- Assignments: Regular assignments that involve practical data analysis tasks and problem-solving exercises.
- Class participation: Active participation in seminars, workshops, and group discussions to enhance learning through interaction.
- Peer reviews: Opportunities to review and provide feedback on classmates' work, promoting collaborative learning.
Summative assessments
Summative assessments occur at the end of each module. They're designed to evaluate your overall comprehension and mastery of the course content.
These assessments will contribute to your final grade.
Examples of summative assessments include:
- Coursework: Projects where you apply the skills and knowledge gained throughout the course to a real-world AI problem.
- Presentations: Oral presentations of your projects and research findings to assess your communication skills and ability to articulate complex ideas clearly.
There'll be no written exams during your AI MSc.
Students will have access to computing resources to support hands-on work.
These tools enable students to tackle real-world challenges and explore practical applications of AI and data analysis.
Whether through cloud-based platforms or high-performance computing environments, the specific setup will be confirmed ahead of the project or module launch.
The School of Computing has a dedicated Wellbeing Advisor who understands the needs of our students.
They can be a confidential listening ear and provide guidance on a range of wellbeing issues.
Throughout your studies, you’ll have access to support from:
- academic staff
- personal tutors and research supervisors
- our University Student Services Team
- student representatives
- peers
You'll also be assigned an academic member of staff, who will be your personal tutor throughout your time with us. They can help with academic and personal issues.
Your teaching and learning is also supported by Canvas. Canvas is a Virtual Learning Environment. You'll use Canvas to submit your assignments and access your:
- module handbooks
- course materials
- groups
- course announcements and notifications
- written feedback
The staff delivering this course are internationally recognised for their contributions to artificial intelligence. Many of them have extensive experience working in the industry and academia.
Our teaching staff belong to academic research groups including:
- Scalable Group, including the Northern Visualization and Visual Analytics research lab
- Networked and Ubiquitous Systems Engineering (NUSE), including the National Edge AI Hub
We also have direct partnerships with the National Innovation Centre for Data and The Alan Turing Institute.
Search our academic staff in the School of Computing
Philip Robinson Library (Student Texts Collection)
Your development
You'll strengthen your research skills through an extended research project, which may include:
- carrying out a literature review
- defining and specifying complex data-related problems
- designing suitable solutions
- implementing models and systems
- critically analysing results and performance
You will also develop practical expertise by engaging with real-world challenges in AI.
You'll apply statistical methods, machine learning, and deep learning techniques to a variety of data types.
The course will also provide hands-on experience in data visualisation, natural language processing, and computer vision, preparing you to work effectively with complex and diverse data.
Upon completing the course, you will be able to:
- design and implement intelligent software systems for data-driven tasks
- apply computing, mathematical, and statistical techniques to data storage and analysis
- confidently use modern programming languages, libraries, and AI frameworks
- build, train, and evaluate predictive models across a range of data domains
Course information: Disclaimers, policies and changes
Previous: OverviewNext: Entry requirements
Entry requirements
The entrance requirements below apply to 2026 entry.
Academic entry requirements
A 2:1 BSc honours degree, or international equivalent, in:
- computer science
- mathematics
- statistics
- an engineering discipline with programming experience
We have a strong track record of admitting applicants from a non-standard background and individuals with strong relevant work experience are encouraged to apply and will be considered on an individual basis.
Qualifications from outside the UK
Select your country
English Language requirements
Select your qualification IELTSPearsonsDuolingo English TestTOEFLOtherPre-Sessional Entry - 6 weeksPre-Sessional Entry - 10 weeks
Previous: Course detailsNext: Careers
Your future
Careers
The course prepares you for a wide range of careers such as:
- AI Engineer
- Machine Learning Engineer
- AI Specialist
- AI Product Manager
- AI Solutions Architect
- Software Engineer
- Data Scientist
Graduates from this course have undertaken various roles including:
- Senior Software Engineer at Sage
- Data Analyst at Vodafone
- Data Engineer at Virgin Atlantic
- Data Scientist at Stanley Black & Decker, Inc.
Industry links
The Industrial Advisory Board (IAB) provides strategic advice and industry insights to support the development, implementation, and continuous improvement of the programme. The IAB includes representatives from:
- Meta
- The Alan Turing Institute
- Airbus
- Defence Science and Technology Laboratory (DSTL)
- JP Morgan
- Lloyds Bank
- PwC
- National Innovation Centre for Data (NICD)
These connections provide you with numerous benefits, including internship opportunities, guest lectures, potential employment upon graduation and industry-sponsored projects.
Recent industry-sponsored projects include:
- Sage: Investigating Interpretability Methods for Visually Rich Document Understanding Models
- Oliver Wyman: Analysing the Performance of a Language Agnostic Version of a Classifier Model Leveraging LLMs
- NICD: Efficient Federated Learning: Analyzing Model Compression for Techniques Bandwidth Optimization
Further study
This course provides a route into PhD level study, offering a robust foundation in both theoretical and applied aspects of Data Science. As a graduate, you'll be prepared to pursue advanced research opportunities and contribute to the academic community through doctoral programs.
Postgraduate research degrees in computer science
AI careers support
Our dedicated careers support team offers specialised guidance tailored to AI students. This includes:
- career planning
- workshops on resume-building and interview techniques
- networking events with industry leaders
- job fairs focused on AI analytics
- access to an extensive alumni network for mentorship and job referrals
- support for start-ups
Our Careers Service
Our expert Careers Service is here to help you take the next steps in your professional life. We will support you while you’re studying with us and for up to three years after you graduate.\ \ You will have access to expert one-to-one advice and guidance through our campus careers centre and online, along with digital resources, workshops, networking opportunities, and careers and recruitment events.\ \ We’ve been awarded 5 QS Stars for Student Employability (2025). Many of our degrees are shaped by strong links with national and international businesses. We are committed to helping you access real-world experience opportunities and develop key skills through paid work placements and internships.
Visit our Careers Service website
The University’s support services, such as career advice, internships, and networking opportunities, have further clarified my career path. I am currently doing an internship as a machine learning intern with Train Air Ltd. I secured this opportunity through the NCL Internship Scheme.
Previous: Entry requirementsNext: Facilities
Facilities
Data visualisation technology
The School of Computing has cutting-edge technology to support research in data visualisation such as:
- a stereoscopic wall display
- a large touchscreen display
- eye trackers
- hand-tracking devices
- VR headsets
National Edge AI Hub
Newcastle University will lead a new national artificial intelligence hub, called the National Edge AI Hub. It'll deliver next-generation innovations and technologies via edge computing.
The School of Computing will host one of the nine hubs in the UK. They're set to unveil groundbreaking AI technologies as part of a coordinated investment by UKRI and the UK government.
You will have an opportunity to work with staff involved in this project and be part of the evolution of AI in the UK.
Continue reading about the National Edge AI Hub
National Innovation Centre for Data
The Newcastle Helix campus is home to the UK’s National Innovation Centre for Data (NICD). NICD runs projects with organisations to help them acquire new skills and innovate through data.
Urban Sciences Building
The School of Computing is based in the £58 million Urban Sciences Building (USB), a flagship development located on the £350 million Newcastle Helix regeneration site in the heart of Newcastle. It brings together:
- academia
- the public sector
- communities
- business and industry
Explore the Urban Sciences Building
Learn more about the Newcastle Helix
Postgraduate student facilities
As a Master's student, you'll have access to specialist teaching spaces and facilities in the USB. These are only available to postgraduate students.
Wellbeing and inclusivity are at the heart of our School. The USB has several wellbeing spaces for students, including:
- The Retreat: A sensory space with relaxing stimuli to distract from busy student life.
- Wellbeing room: Designed for relaxation and quiet time. Here you can take a moment to breathe and unwind. It can also be used by students with special medical requirements.
- Prayer room: For all faiths and none, this space can be used for prayer or quiet reflection.
Find out more about our wellbeing and computing facilities
\
Previous: CareersNext: Fees & funding
Fees, Funding and Scholarships
Tuition fees for 2026 entry (per year)
| Qualification: MSc Full time | |
|---|---|
| Home students Full time: 12 months | Tuition fees (per year) £14,500 |
| International students Full time: 12 months | Tuition fees (per year) £31,700 |
As a general principle, you should expect the tuition fee to increase in each subsequent academic year of your course, subject to government regulations on fee increases and in line with inflation.
EU, other EEA and Swiss nationals - tuition fee status
Depending on your residency history, if you’re a student from the EU, other EEA or a Swiss national, with settled or pre-settled status under the EU Settlement Scheme, you’ll normally pay the ‘Home’ tuition fee rate and may be eligible for Student Finance England support.
EU students without settled or pre-settled status will normally be charged fees at the ‘International’ rate and will not be eligible for Student Finance England support. You may be eligible for a scholarship worth 25% off the international fee. Search our funding database.
If you are unsure of your fee status, check out the latest guidance here.
Scholarships
We support our EU and international students by providing a generous range of Vice-Chancellor's automatic and merit-based scholarships. See our searchable postgraduate funding page for more information.
What you're paying for
Tuition fees include the costs of:
- matriculation
- registration
- tuition (or supervision)
- library access
- examination
- re-examination
- graduation
Find out more about:
If you are an international student or a student from the EU, EEA or Switzerland and you need a visa to study in the UK, you may have to pay a deposit.
You can check this in the How to apply section.
If you're applying for funding, always check the funding application deadline. This deadline may be earlier than the application deadline for your course.
For some funding schemes, you need to have received an offer of a place on a course before you can apply for the funding.
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Previous: FacilitiesNext: How to apply
How to apply
Before you start
Start Dates
The course starts in September.
Closing Dates
There is no application closing date for this course. We suggest international students apply at least two months before the course starts. This is so that you have enough time to make the necessary arrangements.
Specialised application information
As part of the application process, you are required to include a copy of your CV. Your CV should highlight your relevant prior experience relating to data science, including programming and/or statistics experience. You can attach your CV as a file in the applicant portal.
Deposit
All International students
If you are an international student or a student from the EU, EEA or Switzerland and you need a visa to study in the UK, you must pay a deposit or submit an official letter of sponsorship. The deposit is payable after you receive an offer to study with us. This deposit is non-refundable and will be deducted from your tuition fees when you register. You may also be subject to academic and English language qualification verification, confirmation of funds and credibility interviews.
International students who received an offer before 18 March 2026
- You are required to pay a £1,500 deposit or submit an official letter of sponsorship.
International students Bangladesh, Ghana, Myanmar, Nigeria, Sri Lanka, and Pakistan who received an offer after 18 March 2026
- You are required to pay a deposit of £5,000 or submit an official letter of sponsorship by 01 August 2026.
All International students (excluding those from the markets above) who received an offer after 18 March 2026
- You are required to pay a deposit of £1,500 or submit an official letter of sponsorship by 01 August 2026.
Programme codes
| Qualification: MSc Full time | |
|---|---|
| Full time: 12 months | Programme Code: 5449F |
Using the application portal
The application portal has instructions to guide you through your application. It will tell you what documents you need and how to upload them.
You can choose to start your application, save your details and come back to complete it later.
If you’re ready, you can select Apply Online and you’ll be taken directly to the application portal.
Alternatively you can find out more about applying on our applications and offers pages.
Previous: Fees & fundingNext: Get in touch
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Overseas events
We regularly travel overseas to meet with students interested in studying at Newcastle University.
Visit our events calendar for the latest events
Get in touch
Questions about this course?
If you have specific questions about this course you can contact:
Postgraduate Computing\ Email: computing.admissions@newcastle.ac.uk\ School of Computing \ ncl.ac.uk/computing
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