MSc — 2027 entry AI in Engineering
Artificial Intelligence is transforming the world of engineering. Our AI in Engineering MSc will help you explore how AI supports every stage of the engineering lifecycle, from solving complex challenges to developing innovative solutions. Through individual and group projects you’ll build the knowledge and practical skills to apply AI confidently in the engineering profession.
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Why choose
this course?
- Develop the interdisciplinary expertise increasingly sought by employers, combining engineering knowledge with advanced artificial intelligence skills to solve complex challenges across a range of engineering sectors.
- Apply your learning through individual and team projects based on real-world engineering scenarios.
- Explore emerging AI technologies for design ideation, optimisation and cyber-physical systems, preparing you to contribute to the next generation of intelligent engineering solutions.
- Learn in specialist facilities that span both AI and engineering, from dedicated computing laboratories to engineering and design spaces, giving you opportunities to test ideas, develop solutions and explore AI applications in real-world engineering contexts.
- Benefit from industry engagement opportunities, designed to connect your learning with engineering practice from the start and contribute to the future of AI-integrated engineering.
- Develop the confidence to use AI effectively and responsibly, supported by a strong grounding in engineering principles, ethics, critical review, and professional engineering responsibility. Throughout the programme, you’ll learn to produce robust work that can withstand professional scrutiny.
What you will study
You’ll begin by building a strong foundation in AI systems, exploring topics such as generative AI, agentic AI, and also physics-informed AI alongside core engineering principles. You will also revisit the engineering lifecycle in all its stages from ideation to decommission. You'll also examine the wider challenges of applying AI in engineering, including resilience, sustainability, commercial considerations, intellectual property and social responsibility.
You will learn about the different contributions AI can make across the lifecycle and examine the wider challenges of applying AI in engineering, such as resilience, environmental impact, commercial, intellectual property, social responsibility.
The digital skills developed through the programme are focused on the professional deployment of AI. You will develop the ability to critically evaluate and design effective AI toolchains, applying these skills consistently, robustly and verifiably. You will enhance your professional digital capabilities, enabling you to build and manage workflows that integrate AI with engineering modelling and simulation tools.
Through a series of individual and group projects, you'll apply your knowledge to real engineering challenges and build a portfolio of compelling projects that demonstrates your technical expertise and problem-solving abilities. You'll use AI to generate innovative solutions, evaluate design options and optimise engineering systems, before exploring cyber-physical systems that combine AI with hardware and software to interact with the physical world.
The programme concludes with an independent dissertation, giving you the opportunity to investigate an emerging topic in AI engineering with the support of an academic supervisor and, where appropriate, industry collaborators.
Facilities
You'll have access to a range of specialist facilities that support both the AI and engineering elements of the programme. Our dedicated computer laboratories provide the hardware and industry-standard software needed to develop, test and deploy AI applications throughout your studies.
You'll also use our mechanical and structural engineering labs to explore how AI can be applied to real engineering systems, bridging the gap between digital technologies and physical engineering environments. Our Design Centre provides collaborative spaces where you can develop ideas, work on projects and bring engineering concepts to life.
As a student on this programme, you'll also benefit from planned investment in new robotics laboratories, creating additional opportunities to explore the application of AI in intelligent and autonomous engineering systems.
In Semester one, you will study four 15-credit modules in parallel – three in fundamental context, skills and theory, and your first group project on ‘Ideation and Conceptual Design’.
Semester two consists of two 30-credit modules, back-to-back. The first project module focuses on ‘Optimisation using AI in Engineering’ and the second on ‘Cyber-Physical Systems’.
The structure of our programmes follows clear educational aims that are tailored to each programme. These are all outlined in the programme specifications which include further details such as the learning outcomes:
Modules
Modules listed are indicative, reflecting the information available at the time of publication. Modules are subject to teaching availability, student demand, and/or class size caps.
The University operates a credit framework for all taught courses based on a 15-credit tariff, meaning all modules are comprised of multiples of 15 credits.
Please note that modules are listed by the academic calendar and are reflective of a September start date. For students that start a programme in February, please note that the modules listed as semester two will take place in the spring term and modules listed as semester one will take place in the autumn term.
Course options
Year 1
Semester 1 & 2
Compulsory
This module provides information, guidance and support for developing the student¿s employability.In addition, this module helps students build on their previous skills and generate documents that are required to demonstrate their skill sets to external parties, recruiters and recruiting agencies. Furthermore, skills acquired in this module will enable students to actively participate in placement and employment searches.
View full module detailsModule selection for Year 1 (full-time with placement - 2 years) - FHEQ Level 7
As part of the approval process the following new modules have been developed and will be added to the programme once available:
Engineering Lifecycle and AI
AI Concepts and Methods
Digital Skills for AI Deployment
Conceptual Design and AI-driven Ideation
Optimisation with AI in Engineering
Cyber-Physical Systems and Digital Twins
Dissertation (AI in Engineering)
Year 2
Across academic years
Compulsory
This module supports students¿ development of personal and professional attitudes and abilities appropriate to an industrial practice training placement and provides a portfolio of professional development appropriate to the expectations of the graduate¿s technical discipline. It supports and facilitates self-reflection and transfer of learning from student¿s industrial placement experiences to their future employment, maximising the potential to succeed in the global job market. The industrial practice module is concerned with personal and professional development towards holistic academic and non-academic learning, and is a process that involves self-reflection, documented via the creation of a personal record, planning and monitoring progress towards the achievement of personal objectives. Through industrial placement, students not only become resourceful and resilient through exercising to engage effectively with different opportunities and challenges at work but also gain an appreciation and understanding of global, social and ethical issues in the civil engineering industry. This also supports students' development in digital capabilities/literacy. Through working on practice-based projects/problems, they gain knowledge and understanding of sustainability and civil engineers' role and contribution to achieving UN SDGs (Sustainable Development Goals).Development and learning may occur before and during the placement, and this is reflected in the assessment model as a progressive process. However, the graded assessment takes place primarily towards the end of the placement. Additionally, the module aims to enable students to evidence and evaluate their placement experiences and transfer that learning to other situations through written and presentation skills.
View full module detailsTeaching and learning
- Group work
- Independent study
- Laboratory work
- Lectures
- Practical sessions
- Project work
- Seminars
- Research work
- Tutorials
- Workshops
General course information
Contact hours
Contact hours can vary across our modules. Full details of the contact hours for each module are available from the University of Surrey's module catalogue. See the modules section for more information.
Timetable
New students will receive their personalised timetable during Welcome Week. In later semesters, at least one week before the start of the semester.
Scheduled teaching can take place on any day of the week (Monday – Friday), with part-time classes normally scheduled for one or two days. Wednesday afternoons tend to be for sports and cultural activities.
View our code of practice for the scheduling of teaching and assessment (PDF) for more information.
Location
This course is based at Stag Hill campus. Stag Hill is the University's main campus and where the majority of our courses are taught.
We offer careers information, advice and guidance to all students whilst studying with us, which is extended to our alumni for three years after leaving the University.
UK qualifications
A minimum of a 2:2 UK honours degree in an engineering subject.
Applicants with a degree in a non-engineering science or technology subject may also be considered, subject to assessment by the department.
English language requirements
IELTS Academic: 6.5 overall with 6.0 in writing and 5.5 in each other element.
These are the English language qualifications and levels that we can accept.
If you do not currently meet the level required for your programme, we offer intensive pre-sessional English language courses, designed to take you to the level of English ability and skill required for your studies here.
Credit Transfer and Recognition of Prior Learning
We recognise that many students enter their course with valuable knowledge and skills developed through a range of ways.
If this applies to you, the recognition of prior learning process may mean you can join a course without the formal entry requirements, or at a point appropriate to your previous learning and experience.
There are restrictions on some courses, and fees may be payable for certain claims. Please contact the Admissions team with any queries.
Scholarships and bursaries
Discover what scholarships and bursaries are available to support your studies.
Fees per year
Explore UKCISA’s website for more information if you are unsure whether you are a UK or overseas student. View the list of fees for all postgraduate courses.
Fee options
- UK
- £13,400
- Overseas
- £26,900
- UK
- £14,700
- Overseas
- £28,200
- The fee for the placement pathway will be charged in Year 1 of the programme and a fee of £1,850 is payable in Year 2 of the programme
- Once enrolled, students who decide to change from the two-year with placement course to the one-year full time course will not be entitled to a refund of the difference in course fees between the one-year full time course and the first year of the two-year with placement course
- Fees for part-time routes are applicable in each year of the course
- These fees apply to the academic year 2027-28 only. Fees are reviewed annually, and tuition fees may increase for courses running over more than one year.
Read our tuition fees guidance to find out more about payment schedules and how to pay.
Additional costs
Find out more about additional costs that may be incurred during your time at Surrey.
Funding
You may be able to borrow money to help pay your tuition fees and support you with your living costs. Find out more about postgraduate student finance.
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Register your interestAdmissions information
Once you apply, you can expect to hear back from us within 14 days. This might be with a decision on your application or with a request for further information.
Our code of practice for postgraduate taught admissions explains how the Admissions team considers applications and admits students. Read our postgraduate applicant guidance for more information on applying.
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When you accept an offer to study at the University of Surrey, you will be agreeing to follow our policies and procedures, student regulations, and terms and conditions.
We provide these terms and conditions at the offer stage. You will be asked to accept these when you accept the offer made to you. You will be provided with these terms and conditions again at registration by way of reminder.
Disclaimer
This online prospectus has been published in advance of the academic year to which it applies.
Whilst we have done everything possible to ensure this information is accurate; some changes may happen between publishing and the start of the course.