Artificial Intelligence MSc
Queen Mary University of London, United Kingdom
Master of Science in Artificial Intelligence
Queen Mary University of London
Artificial Intelligence
Program Overview: MSc Artificial Intelligence at Queen Mary
The MSc Artificial Intelligence at Queen Mary University of London is designed to equip you with advanced knowledge and practical skills across a broad range of AI topics, from machine learning fundamentals to cutting-edge deep learning and large language models. This programme allows you to focus your studies and combine different AI topics to suit your personal requirements and future career plans.
You will study universal machine learning tools essential for any AI job profile, as well as specific practical and research skills across various AI topics. The programme provides hands-on experience with tools such as Deep Neural Networks, Deep Reinforcement Learning, and Large Language Models through regular exercises and practical labs.
Delivered by the School of Electronic Engineering and Computer Science, the programme benefits from Queen Mary's strong research reputation, including faculty who are Fellows of the Alan Turing Institute. The programme is structured in two specialist streams, allowing you to tailor your learning toward either Language and Intelligent Agents or Computer Vision and Creative Domains.
Key Program Highlights
- Ranked 8th in the UK and top 100 in the world for Artificial Intelligence and Data Science (QS Rankings by Subject 2026)
- Accredited by BCS, The Chartered Institute for IT, and the Institution of Engineering and Technology (IET)
- 100% of graduates from this programme are in highly skilled employment 15 months after graduation
- Taught at Mile End campus, the largest self-contained residential campus in London, with excellent research facilities
Curriculum and Modules
The MSc Artificial Intelligence is structured around compulsory core modules covering the fundamentals of machine learning, AI, natural language processing, and ethics in digital information processing. In addition, you choose one of two specialist streams during Welcome Week based on your interests, and complete a major individual project on your chosen AI specialisation.
Machine Learning
15 creditsCovers the fundamental principles and techniques of machine learning, including supervised and unsupervised learning, model evaluation, and practical implementation using industry-standard tools and libraries.
Artificial Intelligence
15 creditsExplores core AI concepts including search algorithms, knowledge representation, reasoning, and planning. Provides a solid theoretical foundation for understanding intelligent systems.
Natural Language Processing
15 creditsIntroduces techniques for processing and understanding human language, including text classification, sentiment analysis, and working with large language models for various NLP tasks.
Ethics, Regulation, and Law in Digital Information Processing
15 creditsExamines the ethical, legal, and regulatory dimensions of AI and digital information systems, covering topics such as data privacy, algorithmic bias, transparency, and accountability in AI decision-making.
Deep Learning
15 creditsProvides in-depth study of deep neural network architectures, including convolutional neural networks, recurrent neural networks, and generative models, with practical experience building and training deep learning systems.
MSc Individual Project (Dissertation)
60 creditsA major independent research project where you work closely with a supervisor to investigate an AI topic of your choice. The dissertation typically comprises 10,000 to 15,000 words and demonstrates your ability to apply AI techniques to a real-world problem.
Specialist Stream Electives
Admission Requirements
The MSc Artificial Intelligence programme at Queen Mary welcomes applications from graduates with a strong background in computing, engineering, mathematics, or a related technical discipline. All applications are processed through Uni4Edu, which provides personalised guidance throughout the admissions process.
Academic Requirements
- Undergraduate DegreeA 2:1 honours degree (or international equivalent) in Computer Science, Engineering, Mathematics, or a closely related STEM discipline
- Minimum GradeUK 2:1 equivalent (approximately 60% or above); candidates with a strong 2:2 and relevant experience may be considered
- Technical BackgroundStrong foundation in programming and mathematics is expected; prior experience with Python or similar languages is advantageous
- International QualificationsInternational qualifications are assessed on a country-by-country basis; contact Uni4Edu for guidance on your specific qualifications
- Work ExperienceNot required, but relevant professional or research experience in computing or AI may strengthen your application
English Language Requirements
- IELTSOverall 6.5 with minimum 6.0 in each component
- TOEFL iBTOverall 92 with minimum 20 in each component
- PTE AcademicOverall 62 with minimum 56 in each component
Required Documents
Application Deadlines
For personalized admission guidance, document verification, and application support, please contact Uni4Edu
Scholarships and Funding
Queen Mary University of London offers several funding opportunities for students on the MSc Artificial Intelligence programme. Prospective students are encouraged to contact Uni4Edu early to explore all available funding options and receive guidance on scholarship applications.
Google DeepMind Scholarship
Full tuition fees, living allowance, travel grant, and equipment grantAvailable to underrepresented groups in AI, including women and Black students. Scholars also receive mentorship from Google DeepMind employees and opportunities to attend leading AI conferences and events. Contact Uni4Edu to check eligibility and apply.
Queen Mary Alumni Loyalty Discount
Up to 20% tuition fee reductionQueen Mary alumni may be eligible for a tuition fee discount of up to 20% depending on the programme of study. Contact Uni4Edu to confirm your eligibility and the applicable discount amount.
For detailed tuition fee information, please contact Uni4Edu — we will guide you through the costs and available funding options for this program.
Career Prospects
Graduates of the MSc Artificial Intelligence programme are highly sought after across a wide range of industries. The demand for qualified AI experts continues to grow rapidly, with AI jobs among the highest paid in the technology sector. Queen Mary's Careers and Enterprise service provides tailored support including CV workshops, networking events, and access to graduate opportunities.
Potential Career Roles
Where Graduates Work
Rankings and Recognition
Queen Mary University of London is a member of the prestigious Russell Group of research-intensive UK universities and has achieved significant recognition in global rankings. The university has climbed substantially in recent years, reflecting its growing reputation for research excellence and graduate outcomes.
| Subject | Ranking Body | Rank |
|---|---|---|
| Artificial Intelligence and Data Science | QS Rankings by Subject | 8th in UK / Top 100 globally |
| Engineering and Computer Science | THE Subject Rankings | 126–150 globally |
| Computer Science | Complete University Guide | Contact Uni4Edu for current data |
| Research Quality | Complete University Guide | 16th in the UK |
How to Apply
Applying for this program is easy with Uni4Edu. Our team will guide you through every step of the process — from document preparation to final enrolment.
Contact Uni4Edu
Reach out to our team via email or phone. We will assess your profile and confirm your eligibility for this program.
Prepare Your Documents
Our advisors will provide you with a personalised checklist of required documents and help you prepare your application package.
Submit Your Application
Uni4Edu will submit your application on your behalf and keep you updated on its progress throughout the review period.
Receive Your Offer
Once accepted, we will help you understand your offer, arrange visa support if needed, and guide you through the enrolment process.
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