Advanced Artificial Intelligence MSc

Overview

Artificial intelligence (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:

• Google
• 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

Important information

We've highlighted important information about your course. Please take note of any deadlines.

Your course and study experience - disclaimers and terms and conditions

Please rest assured we make all reasonable efforts to provide you with the programmes, services and facilities described. However, it may be necessary to make changes due to significant disruption, for example in response to Covid-19.

View our Academic experience page, which gives information about your Newcastle University study experience for the academic year 2025-26.

See our terms and conditions and student complaints information, which gives details of circumstances that may lead to changes to programmes, modules or University services.

 

Qualifications explained

Find out about the different qualification options for this course.

MSc - Master of Science

An MSc is a taught Master’s degree. It usually involves the study of a science-related subject.

You'll usually study an MSc full-time over 12 months.

A Master of Science is typically awarded for the successful completion of 100 credits of taught modules and an 80-credit dissertation or research project.

Find out about different types of postgraduate qualifications.

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.

Course content changes

Module information is intended to provide an example of what you will study.

Our teaching is informed by research. Course content changes periodically to reflect developments in the discipline, the requirements of external bodies and partners, and student feedback.

Full details of the modules on offer will be published through the Programme Regulations and Specifications ahead of each academic year. This usually happens in May.

To find out more please see our terms and conditions.

Optional modules availability

Some courses have optional modules. Student demand for optional modules may affect availability.

 

Data Science and AI 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

Delivery and teaching methods

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

Assessment methods

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.

Support

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.

Wellbeing advisor support

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.

Student Support

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

 

Our staff

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

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

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:

• Google
• 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.

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 Careers Service is one of the largest and best in the country, and we have strong links with employers. 

Visit our Careers Service website

Quality and ranking

All professional accreditations are reviewed regularly by their professional body

Recognition of professional qualifications outside of the UK

From 1 January 2021 there is an update to the way professional qualifications are recognised by countries outside of the UK

Check the government’s website for more information.

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.

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

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.

Fees and funding

Tuition fees for 2026 entry (per year)

Tuition fee increases

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:

• living costs
• tuition fees

Deposit

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.

Funding deadlines

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.

Search for funding

Find funding available for your course

Select your country

How to apply

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.

Apply Online  

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