MSc in Applied Artificial Intelligence
Bedford, United Kingdom
MSc
DURATION
3 years
LANGUAGES
English
PACE
Full time, Part time
APPLICATION DEADLINE
21 Sep 2026*
EARLIEST START DATE
Sep 2026
TUITION FEES
GBP 29,025 **
STUDY FORMAT
On-Campus
* for UK and Irish students
** for overseas students | £13,005 - for home students
Key Summary
About: The MSc in Applied Artificial Intelligence at Cranfield teaches theoretical and practical skills to apply AI, machine vision and computer science to engineering problems. You’ll study logic and reasoning, data analytics, deep learning, agent architectures, systems engineering and ethical considerations for real-world AI deployment, drawing on Cranfield’s technology and management expertise.
Career Outcomes: Graduates find roles across security, defense, marine, environmental and aerospace sectors and in global primes and start-ups. Typical positions include Autonomous systems engineer, Machine learning engineer, Applied machine learning engineer, Data scientist, Research scientist and Big data engineer. Some continue to PhD study for advanced research training.
Artificial intelligence technologies are being increasingly adopted across a broad range of industries, creating demand for talented graduates who can help realise the transformative potential of AI. With a fundamental interest in AI, machine vision and computer sciences, you will have the desire to apply this knowledge to solve real-world engineering problems.
Taught through a unique combination of theoretical and practical-based sessions, you will cover subjects in logic and reasoning, data analytics, deep learning, agent architectures, alongside the broader systems engineering and ethical considerations required for implementation in real-world systems.
Compulsory Modules
All the modules in the following list need to be taken as part of this course.
- Data Analytics and Visualisation
- Deep Learning for Autonomous Decision Making
- Deep Learning for Computer Vision
- Ethical, Regulatory and Social Aspects of AI
- Multi-Agent Systems
- Search and Optimisation
- Smart Cyber-Physical Systems
- Statistical Learning Methods
- Cranfield University has been ranked amongst the world’s top universities in the latest QS World University Rankings by Subject.
- In Engineering – Mechanical, Aeronautical and Manufacturing, Cranfield has been ranked 27th in the world and attained top scores in Employer and Academic Reputation.
To help students find appropriate funding, we have created a funding finder where you can search for suitable sources of funding by filtering the results to suit your needs. Visit the funding finder.
ASEAN-UK: Women in STEM Scholarships
Cranfield University is proud to join the Women in STEM Scholarship initiative by offering six fully funded scholarships for female students from selected countries in East Asia. We are looking for women with a background in STEM who can demonstrate their need for financial support and who wish to inspire future generations of women to pursue careers in STEM.
Cranfield University GREAT Scholarship
In partnership with the British Council and the GREAT Britain Campaign, Cranfield University is offering 5 scholarships of financial support to the value of £10,000 to students from Bangladesh, India, Kenya, Thailand and Vietnam.
Postgraduate Loan from Student Finance England
A Postgraduate Loan is now available for UK applicants to help you pay for your master’s course.
Chevening Scholarships
Chevening Scholarships are awarded to outstanding emerging leaders to pursue a one-year master’s at Cranfield University. The scholarship includes tuition fees, travel and a monthly stipend for master’s study.
Commonwealth Scholarships for Developing Countries
Students from developing countries who would not otherwise be able to study in the UK can apply for a Commonwealth Scholarship which includes tuition fees, travel and a monthly stipend for master’s study.
Your career
The industry-led education makes Cranfield graduates some of the most desirable all over the world for recruitment by both global primes to smaller innovative start-ups looking for the brightest talent.
Graduates from this course will be equipped with the advanced skills which could be applied to the security, defence, marine, environmental and aerospace industries. This approach offers you a wide range of career choices with job roles including:
- Autonomous systems engineer
- Machine learning engineer
- Applied machine learning engineer
- Data scientist
- Research scientist
- Big data engineer
Others decide to continue their education through PhD studies available at Cranfield University or elsewhere.
This course provides engineering, physics, computing or mathematics graduates with the advanced skills which can be applied to the security, defence, marine, environmental and aerospace industries.
This course is also available on a part-time basis, enabling you to combine studying with full-time employment.
Why this course?
Artificial intelligence (AI) and machine learning are redefining the way we live and work, allowing us to automate processes and enhance productivity. These new technologies create the need for skilled engineers with an understanding of their applications and intricacies.
Increasingly, governments are outlining AI and data revolutions as areas of priority to ensure global leadership for the industries of the future. By embedding AI, government agendas aspire to create new, high-quality jobs and drive economic growth.
Undertaking this course will allow you to be at the forefront of this ongoing technological revolution, equipping you with both the theoretical and practical knowledge to work across disciplines and implement AI systems where they are needed.
We are well located for visiting part-time students from all over the world, and offer a range of library and support facilities to support your studies, while balancing work/life commitments. Our MSc programmes benefit from a broad cultural diversity of students, which significantly enhances the learning experience for both staff and students.
The course will include eight taught compulsory modules, which are generally delivered from October to March.
Students are also supported in their learning and personal development through participation in: industry seminars, group poster sessions, group discussions, group presentations, video demonstrations, case studies, laboratory experiments, coursework and project work. Students will receive hands-on experience accessing equipment and facilities within both our Aerospace Integration Research Centre and Intelligent Mobility Engineering Centre.
The new MSc in Applied Artificial Intelligence will use standard teaching and assessment methods as well as technology-enhanced teaching (TET) methods such as a Virtual Learning Environment (VLE) to support different learning styles. Theories and fundamentals of AI will be taught in both lecture and workshop formats, where videos and technology demonstrators will be used as teaching aids. Lecture videos will be available on VLE to provide an interactive learning experience.
Taught modules 40%, group project 20%, individual research project 40%
Group Project
The aim of the group design project (GDP) is for students to design, implement, validate and test an AI-based system, showing an understanding of how to apply the knowledge acquired in the taught modules and integrate the various concepts. The GDP will provide invaluable experience of delivering a project within an industry-structured team, developing transferable skills including teamwork with members with diverse backgrounds and expertise, project management and technical presentations.
Some recent projects include:
- Creating Explainable Interfaces for Autonomous Flight.
- Mapping Illegal Pollution in Cities using Drones with an Electronic Nose.
- Causal Curiosity using a Robot with Digital Mind.
- Dynamic Contention Pricing in Future Airspace Management.
- Violence Detection at Airports.
- Enhancing Airport Safety Using Crowd Monitoring and Social Distancing Analysis.
- Detection of Vital Signs of Myocardial Infarction Using Computer Vision and Edge AI.
Part-time students are encouraged to participate in a group project as it provides a wealth of learning opportunities. However, an option of an individual dissertation is available if agreed with the Course Director.
Individual Project
The individual research project allows you to delve deeper into an area of specific interest. It is very common for industrial partners to put forward real-world problems or areas of development as potential research thesis topics. For part-time students, it is common that their research thesis is undertaken in collaboration with their place of work.
Some recent projects include:
- Causal Learning in Unmanned/Autonomous Vehicle Dynamics.
- Eyes-Out Airborne object detection module improving pilots Situational Awareness.
- Light-weight Deep Learning Approaches for Early Detection of Wildfire and Smoke for UAV Applications.
- Cypher Key Generation Using Graph Layer Security and Federated Multi-Agent Deep Reinforcement Learning.
- Generation of Realistic Images from 3D Simulated Environment using Conditional GAN.
- Deep Autoencoders for Unsupervised Anomaly Detection in Wildfire Prediction.
- Large Language Models for Drone Navigation.
- Autonomous systems applications of Large Language models.
- Generative Modelling for Improved Situational Awareness.
- Drone camera and digital map alignment using an Augmented Reality.