Artificial Intelligence MSc
Why choose this course?
Study a masters in this rapidly evolving field. You'll gain a strong foundation in AI technologies and their application in the real world.
Modules are designed to align with the growing market opportunities in various areas, including big data, data mining, machine learning, deep learning and their direct application in Computer Vision, Natural Language Processing, and Cyber Security.
Please note: this course is still subject to validation. Some course information may not be available at this time.
| Mode | Duration | Start date |
|---|---|---|
| Full time | 1 year |
September 2024 January 2025 |
| Full time | 2 years including professional placement |
September 2024 January 2025 |
| Part time | 2 years |
September 2024 January 2025 |
Please note: this course is still subject to validation.
Please note: Teaching on this course may take place on more than one KU campus.
| Main location | Penrhyn Road |
Reasons to choose Kingston University
- Gain skills in an area that is in demand, both in industry and in the public sector.
- Tailor your degree to your interests, with optional modules in specialist areas of AI.
- Through a project dissertation, you will study an area of interest in depth. This can offer valuable industry experience.
What you will study
Year 1
Professional placement
Core modules
Applied Data Programming
30 credits
This module emphasises a practical and applied approach to programming and software skills for data scientists which differs from typical software engineering approaches in that the emphasis is on the use and manipulation of data using languages and platforms designed for use in real-life, data-driven problems. The languages and platforms are considered only as far as their use for data manipulation are needed with limited exploration of underlying theory or data structures. This prioritises practical implementation including locating, accessing, loading, manipulating, securing, storing and describing data, and enables the introduction of aspects of data analysis, data-mining and machine learning provided by the chosen languages and platforms.
Big Data and Data Mining
15 credits
Ethics and Regulation of Artificial Intelligence
15 credits
Machine Learning and Artificial Intelligence
30 credits
The module introduces fundamental concepts and methods in Machine Learning and Pattern Recognition, and discusses their applications in disciplines such as image and video analysis, computer games, information security, data science and mechatronics. Students are firstly introduced to classical methods, before they are taught modern state-of-the-art approaches. Then, they are exposed to applications related to their course. The module is taught in a practical fashion and therefore some knowledge of a programming language is required.
Project Dissertation
60 credits
This module constitutes the major individual piece of work of the masters programme where you will carry out a project involving independent critical research, design and implementation (where applicable).
Optional modules (choose 2)
Computer Vision
15 credits
Cyber Security and Artificial Intelligence Applications
15 credits
Natural Language Processing
15 credits
Professional placement
Professional Placement
120 credits
The Professional Placement module is a core module if you're following a masters programme that incorporates an extended professional placement. It provides you with the opportunity to apply your knowledge and skills in an appropriate working environment, and develops and enhances key employability and subject specific skills in your chosen discipline. You may wish to use the placement experience as a platform for a major project or your future career.
It is your responsibility to find and secure a suitable placement opportunity; this should not normally involve more than two placements which must be completed over a minimum period of 10 months and within a maximum of 12 months. The placement must be approved by your Course Leader prior to commencement to ensure its suitability. You will have access to the standard placement preparation activities offered by the Student Engagement and Enhancement (SEE) group.
Read more about the postgraduate work placement scheme.
Artificial Intelligence MSc offers a comprehensive range of modules that cover cutting-edge algorithms, tools, and techniques in the field of AI. These modules are designed to align with the growing market opportunities in various areas, including big data, data mining, machine learning, deep learning and their direct application in Computer Vision, Natural Language Processing, and Cyber Security.
Modules are structured in a way that follows the typical roadmap of an AI project, ensuring a systematic approach to learning. Elective modules allow you to specialise and focus on specific areas of interest.
Work placement scheme
Many postgraduate courses at Kingston University allow students to take the option of a 12-month work placement as part of their course. Although the University supports students in finding a placement and organises events to meet potential employers, the responsibility for finding the work placement is with the student; we cannot guarantee the placement, just the opportunity to undertake it. You may find securing a professional placement difficult as they are highly competitive and challenging, but they are also incredibly rewarding. It is very important to prepare and apply yourself if this is the route you wish to take. Employers look for great written and oral communication skills and an excellent CV/portfolio. As the work placement is an assessed part of the course, it is covered by a student's Student Route visa.
Find out more about the postgraduate work placement scheme.
Who teaches this course?
Our modern teaching environment at Kingston University
There is a wide range of facilities at our Penrhyn Road campus, where this course is based. You will have access to a modern environment with the latest equipment, including:
- dedicated postgraduate computing laboratories, fully-equipped with fold-flat LCD screens, data-projection systems and high-spec processors
- industry-standard development software and tools, such as Python, Scikit, Learn and Tensorflow
- the learning resources centre, offering subject libraries, online database subscriptions and resource materials.
Our dedicated team of IT technicians supports the labs and is always on-hand to provide assistance.
Resources in London
Kingston is just a 30-minute train journey from central London, where you can access a wealth of additional libraries and archives, including the British Library and the Institute of Engineering and Technology.
Course fees and funding
Here you can find more details about fees for this course, as well as any funding opportunities available to you for this course. Please note that fees relate to the academic year in question and will increase in future years.
If you require a Student Route visa to reside in the UK you may not be able to enrol on a part-time programme at the University.
Kingston University has carefully considered the Student Route visa and has decided not to offer Student Route visa part-time study. Student Route visa sponsorship is only available to students studying on a full-time course.
Additional costs
Depending on the programme of study, there may be extra costs that are not covered by tuition fees which students will need to consider when planning their studies. Tuition fees cover the cost of your teaching, assessment and operating University facilities such as the library, access to shared IT equipment and other support services. Accommodation and living costs are not included in our fees.
Where a course has additional expenses, we make every effort to highlight them. These may include optional field trips, materials (e.g. art, design, engineering), security checks such as DBS, uniforms, specialist clothing or professional memberships.
After you graduate
You will be well equipped to work in a variety of industries that are rapidly adopting automation and robotics technology, such as manufacturing, healthcare, logistics, and transportation. You will also be able to contribute to cutting-edge research in the field of robotics.
Course changes and regulations
The information on this page reflects the currently intended course structure and module details. To improve your student experience and the quality of your degree, we may review and change the material information of this course. Course changes explained.
Programme Specifications for the course are published ahead of each academic year.
Regulations governing this course can be found on our website.
