MSc Artificial Intelligence with Large Language Models
Master large language models powering the next generation of AI.
Year of entry: 2026 (September)
The MSc Artificial Intelligence with Large Language Models gives you the skills, insight and hands-on experience to innovate with LLMs, from the theory that underpins them to the systems transforming industries.
You’ll explore how natural language processing evolved from early rule-based systems to today’s multimodal LLMs capable of understanding text, images and more. Through practical labs and real-world projects, you’ll learn how to develop, fine-tune and deploy these models across fields such as healthcare, finance, science and the creative industries.
Unlike broader AI degrees, this course dives deep into the full history and cutting-edge future of language models, preparing you to become a leader in this fast-moving area. By the time you graduate, you’ll not only know how these systems work, you’ll know how to design responsible, explainable and impactful AI solutions that push the boundaries of what’s possible.
Whether you aim to work in AI research, development or innovation, this degree will prepare you to join the next generation of language model engineers driving change across the world.
Course content
Throughout the year, you'll study four core modules and two option modules.
You'll also develop skills to enhance your computational thinking engineering to enable you to succeed in an industrial, academic or research environment. The research project allows you to develop knowledge in a specific area of AI or machine learning, while developing skills to contribute professionally to solving commercial and industrial engineering problems.
Modules
Core Modules
- Natural Language Processing
- Deep Learning
- Research Methods for Computer Science
- Large Language Models
Option Modules
You will study two option modules. Examples can be found below. Some option module combinations may not be possible. The options available to you will be confirmed after you begin your course.
- Engineering LLM-Based Agents and Applications
- Professional & Academic Development
- AI Search and Logic
- Engineering 2: Automated Software Engineering
- Governance of Data Science
- Computer Vision and Graphics
- Autonomous Robots
Our modules may change to reflect the latest academic thinking and expertise of our staff, and in line with Department/School academic planning.
Research project
Work on your individual project will start around the beginning of April, and you will receive regular one-to-one supervisions throughout your project.
You will continue to work on your individual project over the summer, and there will be continuing supervision and research-group meetings to discuss your project. You will finish the course when you hand in your dissertation and paper for your project in September.
Learning outcomes
Every course at York is built on a distinctive set of learning outcomes. These will give you a clear understanding of what you will be able to accomplish at the end of the course and help you explain what you can offer employers. Our academics identify the knowledge, skills, and experiences you'll need upon graduation and then design the course to get you there.
Learning outcomes for this course
- Critically evaluate the theoretical foundations and architectures of large language models and their role within the broader field of artificial intelligence.
- Design, implement and fine-tune large language models for specific tasks across diverse application domains, using state-of-the-art tools and frameworks.
- Apply advanced techniques in natural language processing, including transfer learning and multimodal integration, to solve complex, real-world problems.
- Assess and mitigate ethical, social and environmental risks associated with deploying LLMs, including issues of bias, privacy and misuse.
- Interpret and communicate the outputs and decisions of LLM-based systems using explainability and interpretability methods suitable for technical and non-technical audiences.
- Integrate LLMs into broader AI systems, demonstrating an understanding of how these models interact with other machine learning and knowledge-based components.
- Independently design, execute and evaluate a significant project based on the synthesis and evaluation of up-to-date research literature from related areas, using clearly argued criteria. Findings will be presented in an accurate, accessible, detailed, concise report which details the sustained investigations and is appropriately addressed for a professional audience.
Fees and funding
Annual tuition fees for 2026/27
| Study mode | UK (home) | International and EU |
|---|---|---|
| Full-time (1 year) | £13,900 | £32,900 |
Fees information
UK (home) or international fees? The level of fee that you will be asked to pay depends on whether you're classed as a UK (home) or international student. Check your fee status.
Find out more information about tuition fees and how to pay them.
Funding information
Discover your funding options to help with tuition fees and living costs.
We'll confirm more funding opportunities for students joining us in 2026/27 throughout the year.
If you've successfully completed an undergraduate degree at York you could be eligible for a 10% Masters fee discount.
Funding opportunities
Chevening Scholarships
We are pleased to work with Chevening Scholars to offer funding for our Masters programmes. Chevening Scholarships provide one year of fully-funded postgraduate study in the UK for international (including EU) students. The scholarships are open to early and mid-career professionals who have the potential to become future leaders.
Teaching and assessment
You’ll work with world‐leading academics who’ll challenge you to think independently and excel in all that you do. Our approach to teaching will provide you with the knowledge, opportunities, and support you need to grow and succeed in a global workplace.
Teaching format
Part of the course is taken up by taught modules. Each module comprises a mix of lectures, problem classes and practical classes, plus personal study time. You'll also undertake an individual research project under the supervision of a member of staff.
Throughout the course you will have a personal tutor, who will provide academic and pastoral advice. When you undertake your individual project, you will be allocated a supervisor within your area of interest. You should expect to be working on open assessments during vacation periods.
Due to the intensive nature of the course, you will need to be in York throughout both semesters and over the summer while you undertake your individual project.
Facilities
The Department houses four software and two hardware laboratories.
Our study and social pod is open 24/7 for group and individual study. It can also be booked for student society meetings and for events.
Find out more about our facilities, including a video tour, showing our labs, teaching and research spaces.
Teaching location
Computer Science is based on Campus East. The majority of teaching on this course takes place on Campus East in the Ian Wand building and Ron Cooke Hub.
About our campus
Our beautiful green campus offers a student-friendly setting in which to live and study, within easy reach of the action in the city centre. It's easy to get around campus - everything is within walking or pedalling distance, or you can always use the fast and frequent bus service.
Assessment and feedback
We assess modules in a variety of ways, including practical exercises, reports and closed examinations. Your project assessment will be made up of a dissertation.
Assessments take place at various times during the year. Closed examinations are taken in the three-week assessment periods at the end of each semester.
Practical exercises, reports and other forms of open assessment typically occur towards the end of the teaching sessions of a module. Work for these assessments must be submitted by fixed deadlines normally well after the conclusion of the taught sessions.
Careers and skills
Skills for employability are embedded throughout the programme, with opportunities for you to return to these throughout the degree. Throughout the programmes, you'll study real cases from the industry, learn how to run projects and manage risks.
Career opportunities
- Programming engineer
- Software developer
- Higher education teaching and research
- Information analyst and app developer
- Systems architect
- Business analyst
- Artificial intelligence researcher
Transferable skills
- Advanced computational skills
- Project management and organisation
- Project evaluation
- Communication and time-management skills
- Research skills
Turn ambition into achievement with our expert guidance and connections. From your first day here to life after graduation, we'll help you find your career advantage.
Entry requirements
| Qualification | Typical offer |
|---|---|
| Undergraduate degree | 2:2 or equivalent in Computer Science or a relevant discipline. Successful applicants will demonstrate a strong background in the following essential topics: programming, maths and a knowledge of basic algorithms |
| Other international qualifications | Equivalent qualifications from your country |
English language
If English isn't your first language you may need to provide evidence of your English language ability. We accept the following qualifications:
| Qualification | Minimum requirement |
|---|---|
| IELTS (Academic and Indicator) | 6.5, minimum 6.0 in each component |
| Cambridge CEFR | B2 First: 176, with 169 in each component |
| Oxford ELLT | 7, minimum of 6 in each component |
| Oxford Test of English Advanced | 136, minimum 126 in each component |
| Duolingo | 120, minimum 105 in all other components |
| LanguageCert SELT | B2 with 33/50 in each component |
| LanguageCert Academic | 70 with a minimum of 65 in each component |
| Kaplan Test of English Language | 478-509, with 444-477 in all other components |
| Skills for English | B2: Merit overall, with Pass with Merit in each component |
| PTE Academic | 61, minimum 55 in each component |
| TOEFL | 87, minimum 21 in each component |
| Trinity ISE III | Merit in all requirements |
For more information see our postgraduate English language requirements.
If you haven't met our English language requirements
You may be eligible for one of our pre-sessional English language courses. These courses will provide you with the level of English needed to meet the conditions of your offer.
The length of course you need to take depends on your current English language test scores and how much you need to improve to reach our English language requirements.
After you've accepted your offer to study at York, we'll confirm which pre-sessional course you should apply to via You@York.
Next steps
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