MSc Generative Artificial Intelligence
- Course type
- Postgraduate
- Course qualification
- MSc
Course summary
What is the fee?
For all course options, see fees and funding
Where will I study?
Peel Park campus
How long will I study?
Full-time: One year
Part-time: 28 months
International students accepted?
Yes, available to international students
Overview
This course will equip you with the skills to design, build, and deploy cutting-edge generative AI systems that solve real-world problems. You will move beyond theory to develop practical expertise in large language models (LLMs), multimodal AI, and emerging agentic systems, learning how to take ideas from concept to production.
What makes this course different is its strong focus on applied, industry-relevant AI engineering and deployment. You will not just learn how generative models work – you will learn how to implement them within real organisational constraints, using modern engineering and operational practices such as MLOps and LLMOps. You will also explore the ethical, legal, and societal implications of AI, ensuring you can develop solutions responsibly and confidently from a technical implementation perspective.
This course builds on Salford’s established strengths in AI and data science, combining specialist generative AI content with hands-on learning, practical projects, and industry-informed teaching. By the end, you will have a portfolio of work demonstrating your ability to deliver impactful AI solutions, preparing you for technical and engineering-focused high-demand roles across multiple sectors.
International applicant? Please check international intakes for the latest information and application dates.
You will:
- Design and build generative AI systems using large language models and multimodal architectures
- Apply MLOps and LLMOps practices to deploy and manage AI systems in real-world environments
- Evaluate and optimise AI models using appropriate metrics, testing, and validation techniques
- Address ethical, legal, and societal challenges in responsible AI development
- Develop practical technical solutions to real-world problems through applied projects and case studies
- Build a professional portfolio demonstrating industry-ready generative AI engineering and development skills
This is for you if...
You want to build career-ready skills in generative AI, one of the fastest-growing areas in technology
You want to move beyond theory and learn how to deploy real-world AI systems
You want strong career prospects in roles like AI engineer, consultant, or product specialist
You want to study a specialist MSc focused entirely on generative AI, not general AI
You want hands-on experience with industry-relevant tools, frameworks, and deployment practices
You want to develop a portfolio that demonstrates your ability to deliver impactful AI solutions
School of Science, Engineering and Environment
Rising to the challenge of a changing world, our postgraduate courses are designed to shape the next generation of urbanists, scientists, engineers, consultants and leaders.
Shaped by industry, and delivered by supportive programme teams, you can develop the skills to take your career potential further.
Learning Environment
Our computing suites are equipped with software platforms and languages used in machine learning, data mining, and statistical analysis. These include SAS Enterprise Guide & Miner, Python, Apache Hadoop & Spark, RapidMiner, plus NoSQL databases, such as MongoDB.
Leading the way
The University of Salford is at the forefront of developing AI to revolutionise transport.
Since 2019, the University has pioneered industry-focused research and industry focus through its acquisition of a NAVYA autonomous shuttle, and the creation of the Automotive and Autonomous Vehicle Technology (AAVT) Labs.
Industry collaboration and research
When you start this degree course with Salford, you are joining a community making a difference in industry, our local region and in our wider society.
Many of our academics and technicians who support your course also lead collaborative, interdisciplinary, high-impact work in a range of local and global computing and informatics issues and challenges.
Discover how you are part of something bigger.
How you'll learn
Future careers
EMPLOYMENT
This course prepares you for a wide range of high-demand roles in the rapidly growing field of artificial intelligence. You will graduate with both the technical expertise and practical experience needed to contribute immediately in industry.
Typical career paths include roles such as Generative AI Engineer, Machine Learning Engineer, AI Engineer, Data Scientist, AI Consultant, and AI Product Manager. You may also pursue specialist roles focused on large language models, natural language processing, or multimodal AI systems.
Graduates from related programmes at Salford have gone on to work in organisations across sectors including technology, healthcare, finance, and the public sector. According to a recent LinkedIn report on the fastest-growing jobs in the UK, roles related to artificial intelligence and machine learning continue to rank among the most in-demand and rapidly expanding career paths.
With generative AI skills increasingly in demand across industries, this course will position you to take advantage of emerging opportunities and shape how AI is applied in real-world contexts.
FURTHER STUDY
You might be interested in taking your subject interest further with postgraduate research. The Salford Innovation and Research Centre (SIRC) is home to our Informatics PhD and Research Master’s opportunities in knowledge discovery and semantic web, software engineering, big data, data mining and analytics, cyber security, information visualisation and virtual environments.
Explore our Doctoral School to learn more about research training, support and opportunities.
Modules
Course content
This course gives you a comprehensive, hands-on understanding of generative AI, combining advanced technical knowledge with real-world application. You will study how modern AI systems are designed, built, evaluated, and deployed, with a strong emphasis on practical implementation rather than theory alone.
You will develop expertise in large language models, multimodal AI, and emerging agentic systems, alongside core machine learning foundations. This course also focuses on the operational side of AI, including MLOps and LLMOps, so you can confidently take systems from prototype to production.
You will explore responsible AI practices throughout, including ethics, data governance, and regulatory considerations. Teaching is delivered through lectures, labs, and project-based learning, giving you the opportunity to apply your knowledge to realistic scenarios.
You will complete a major final project, where you will design and deliver a substantial generative AI solution, integrating technical, organisational, and ethical considerations to demonstrate your readiness for industry or further research.
Modules
Machine Learning & Data Mining
You will develop a strong foundation in core machine learning techniques, including supervised and unsupervised learning, model selection, and evaluation. You will work with real datasets using Python, learning how to prepare data, train models, and assess performance. This module ensures you can confidently apply machine learning methods as a basis for more advanced generative AI techniques.
Applied Computer Vision
You will explore modern computer vision techniques, including deep learning approaches such as convolutional neural networks and vision transformers. You will work with image and video data, learning how to build systems for recognition, classification, and generation. This module also introduces multimodal AI, where visual and language models are combined.
Generative AI & Large Language Models
You will study the principles and practice of generative AI, including large language models, diffusion models, and other generative architectures. You will learn how to fine-tune models, design prompts, and build applications such as chatbots and content generation tools. You will also evaluate model outputs and understand the limitations and risks of generative systems.
MLOps & Responsible AI Deployment
You will learn how to deploy, manage, and monitor AI systems in real-world environments. This includes MLOps and LLMOps practices, scalability, performance optimisation, and cost considerations. You will also explore ethical, legal, and societal issues, including bias, transparency, and data protection, ensuring you can develop AI responsibly.
Final Project / Dissertation
You will complete a substantial independent project, applying your knowledge to design and deliver a generative AI solution to a complex problem. You may work with a real organisation or a realistic case study, developing a system from concept through to evaluation. This project enables you to build a strong portfolio piece demonstrating your technical and professional capabilities.
We take a flexible approach to our course delivery that promotes diversity and inclusivity and provides a blended learning experience, which will vary to meet specific programme requirements. This learning time includes formal lectures and interactive activities such as seminars, tutorials, practical sessions, laboratory and studio learning. Smaller classes may be used to support collaborative activities such as project and group work and presentations. A range of different assessments and feedback is offered to meet the needs of both our diverse student body and specific subject needs.
Our postgraduate taught courses are normally made up of 30 credit modules which are equal to 300 hours of learning time, or 15 credit modules which are equal to 150 hours of learning time. A Master’s degree typically comprises 180 credits, a PGDip 120 credits, and a PGCert 60 credits.
Please note that exact modules and content offered may vary in order to keep content current and, for courses that offer optional modules, may depend on the number of students selecting particular options. When accepting your offer of a place to study on a programme with optional modules, you should be aware that optional modules may not all run each year. Your tutor will be able to advise you as to the available options on or before the start of the programme. Whilst the University tries to ensure that you can undertake your preferred options, it cannot guarantee this.
Entry requirements
APPLICANT PROFILE
This course is ideal if you’re excited by the rapid rise of generative AI and want to be part of shaping how it’s used in the real world. You might already have a background in computing, engineering, maths, or another technical field, and now want to specialise in one of the most in-demand areas in tech.
You could also be working in a technical role and looking to move into AI, deepen your expertise, or future-proof your career. If you enjoy problem-solving, building things, and seeing your ideas come to life in practical applications, this course will suit you well.
This programme is right for you if you don’t just want to understand AI – you want to build and deploy practical AI systems. You’re curious about how systems actually work in practice, from building models to deploying them responsibly. If you’re motivated to develop cutting-edge skills, work on real challenges, and graduate ready to make an impact, this course is designed for you.
ENGLISH LANGUAGE REQUIREMENTS
All of our courses are taught and assessed in English. If English is not your first language, you must meet our minimum English language entry requirements. An IELTS score of 6.0 (no element below 5.5) is proof of this, and we also accept a range of equivalent qualifications.
Read more about our English language requirements, including information about pathways that can help you gain entry on to our degree courses.
INTERNATIONAL APPLICATIONS
Please check international intakes for the latest information and application dates.
Standard entry requirements
Undergraduate degree
You will normally need a minimum of a second-class honours degree (2:2 or above) from a recognised university.
Your degree should be in Computer Science or a related STEM subject (such as Mathematics, Engineering, Physics, or Data Science) with a significant programming component. You should be comfortable with at least one programming language (such as Python, Java, or similar) and have some prior experience of computational or analytical problem-solving.
Alternative entry requirements
Accreditation of Prior Learning (APL)
We welcome applications from students who may not have formal/traditional entry criteria but who have relevant experience or the ability to pursue the course successfully.
The Accreditation of Prior Learning (APL) process could help you to make your work and life experience count. The APL process can be used for entry onto courses or to give you exemptions from parts of your course.
Two forms of APL may be used for entry: the Accreditation of Prior Certificated Learning (APCL) or the Accreditation of Prior Experiential Learning (APEL).
For more information about the APL scheme: email enquiries@salford.ac.uk or call 0161 295 4545.
Salford Alternative Entry Scheme (SAES)
We positively welcome applications from students who may not meet the stated entry criteria but who can demonstrate their ability to successfully pursue a programme of study in higher education. Students who do not have the traditional entry requirements may be able to apply through the Salford Alternative Entry Scheme. Support in preparing for the written assessment is available from the University.
Fees and funding
2028/29
| Type of study | Fees |
|---|---|
| Full-time | £10,800 per year |
| Part-time | Part time fees are calculated on a pro rata basis |
2028/29
| Type of study | Fees |
|---|---|
| Full-time | £20,520 per year |
Fees and funding
Find out about how course fees work, and the various loans and financial support schemes available.
Additional costs
You should consider further costs which may include books, stationery, printing, binding and general subsistence on trips and visits.
International student scholarships
If you are a high-achieving international student, you may be eligible for one of our scholarships. Learn more about our latest international scholarships.