The Artificial Intelligence MSc course combines a wide choice of advanced topics in computer science with specialist modules relating to computational intelligence, including logic-based, connectionist and evolutionary artificial intelligence, inspirations from the natural world, practical applications and the philosophy of machine reasoning.
The course is aimed at graduates wanting to launch, or take the next step in their careers You'll be prepared for a career in computing, or a career involving the application of computing and artificial intelligence for problem solving in any professional field
If you start in September, you can choose to take this course with the addition of an year in industry. You can also access this course through an Internationally Incorporated Master's (IIM) specifically designed for the needs of international students.
This degree has been partially accredited by BCS, The Chartered Institute for IT.
A first or second class honours degree or equivalent in computing or a related subject.
All applicants are considered on an individual basis and additional qualifications, professional qualifications and relevant experience may also be taken into account when considering applications.
Please see our International Student website for entry requirements by country and other relevant information. Due to visa restrictions, students who require a student visa to study cannot study part-time unless undertaking a distance or blended-learning programme with no on-campus provision.
This course requires a Good level of English language, equivalent to B2 on CEFR.
Details on how to meet this requirement can be found on our English Language requirements webpage.
Examples:
IELTS 6.0 with a minimum of 5.5 in each component
PTE Academic 63 with a minimum of 59 in each sub-test
A degree from a UK university
A degree from a Majority English Speaking Country
Please note that if you are required to meet an English language condition, we offer a number of pre-sessional courses in English for Academic Purposes through Kent International Pathways.
We’ve created the most progressive approach to higher education, developing and modernising our curriculum. For 2025 our courses will be designed with you at their heart to deliver a top-class student experience and career outcomes.
The following modules are what students will typically study, but this may change year to year in response to new developments and innovations.
The course consists of a collection of compulsory modules covering core topics in the area of artificial intelligence and machine learning. You take all compulsory modules and choose one from a list of optional modules.
At the end of the course you complete your Project and Dissertation.
Artificial Intelligence is an exciting and rapidly advancing technology. The computer language of choice is almost exclusively Python. Python is a powerful language with an unmatched ecosystem of software packages. This module equips the successful student with the tools they need for a life-long career in AI programming and data-driven problem solving. The student will learn the advanced language features required for solving the challenging AI problems. Material includes tools for data manipulation and preparation, AI programming software packages and visualisation tools. All instruction employs the industry standard programming tools universally used for experimentation and result dissemination.
Dive into the exhilarating world of machine learning, where cutting-edge artificial intelligence meets real-world applications. With our comprehensive program, you'll discover how computers can autonomously learn and evolve, harnessing data and active exploration to perfect their algorithms. By mastering these revolutionary techniques, you'll gain the skills to make insightful, effective decisions tailored to a wide array of practical challenges. Our in-depth exploration of key algorithms ensures you not only understand but excel in the intricacies of machine learning, positioning you at the forefront of innovation. Embrace the future - let machine learning elevate your expertise and ambition to new heights.
Embark on a transformative journey into Natural Language Processing (NLP). By delving into the realm of NLP, you will gain a deeper understanding of the intricacies of language-based AI and learn valuable skills that are highly sought after in the tech industry. You’ll learn about how cutting-edge technology is being used in human language understanding and manipulation. Through hands-on practical explorations, you'll discover how to wield powerful NLP tools and libraries to craft artificial intelligence code capable of deciphering human-like text. You’ll find out about the power of language models, from traditional linguistics-influenced methods to state-of-the-art architectures. You’ll become adept at deploying these models critically and successfully, with the opportunity to explore a particular topic in more depth through practical project work.
How do robots work?
You will learn about cognitive robotics, a branch of robotics, where knowledge drives action selection, planning, and execution. The goal is to understand cognitive robot design and develop skills to implement simple tasks using various robots in our lab.
With or without prior robotics experience, you'll learn core robotics principles through hands-on activities with real mobile robots and virtual simulators. You'll learn common software environments to operate mobile robots for navigation and object manipulation. You will be exposed to different applications of the state-of-the-art in Cognitive Robotics, such as industrial robots, collaborative robots, and human-robot interaction. You will be introduced to recent challenges in robotic vision and how robots can use and understand human language. You will explore the societal impact of Socially Assistive Robots, focusing on how their physical bodies enhance interactions compared to virtual agents.
Deep learning is an approach to machine learning developed over the past several decades that draws heavily on our knowledge of the human brain, statistics and applied mathematics. In recent years, deep learning has grown tremendously in popularity and usefulness, largely due to more powerful computers, larger datasets and techniques to train deeper networks.
You will investigate modern deep neural networks starting from the fundamentals of Artificial Neural Networks (ANNs). You will start by learning what is an artificial neuron and architectures like multilayer perceptron, expanding on algorithms for training ANNs such as gradient descent and backpropagation.
You will examine applications of deep learning with particular attention to coding aspects during lectures and practical activities. You will learn to use the most popular techniques to evaluate the performance of a model on real data. For this, you will be introduced to different types of deep neural networks, from convolutional networks to recursive neural networks, and autoencoders to address different problems with a particular focus on computer vision topics.
This module will guide you through the different stages of working on an exciting computer science project. World-leading experts in the field will support you along the way by providing supervision and monitoring of your weekly activities. With computer systems becoming more crucial in everyday life, you’ll have the opportunity to conceptualise, design, develop, and test your own large system capable of solving the identified challenges. Alternatively, you will explore and critically evaluate state of the art literature, identify relevant research methodologies to advance topics in computer science, carry out independent investigations, and make an impact in the research community. You’ll be empowered to explore different skills learned throughout your degree programme and apply them in the specific domain identified for your master’s project. Finally, you will reflect on your project journey throughout the writing of a well-organised dissertation demonstrating your individual reflection and achieved learning.
What does it mean for a computer to be creative? How can artificial intelligence be used to generate creative behaviour? How do we work around the social, ethical and philosophical issues that arise? You’ll learn about key theoretical, practical and philosophical research and issues around computational creativity and creative AI. You will explore what computational creativity is and be given examples to consider in different creative domains. You’ll gain practical experience in writing creative AI software. We’ll also tackle how to evaluate the creativity of creative computer systems and consider contextual issues around how computational creativity and creative AI can be used. Student-led seminars will allow you to develop knowledge by reading about, discussing and reflecting on current issues under debate in the area. You will identify a specific context to focus on in more depth and, in your chosen context, you will conceptualise, design, build and evaluate your own creative AI software.
Quantum technologies are currently being developed that will have a significant impact on society. In this module we will study two particularly promising quantum technologies: quantum computation, and quantum cryptography. The module will begin with an overview of the mathematical and theoretical knowledge required to tackle these more specialised and advanced topics. You will then learn the basic principles of quantum algorithms and quantum cryptography. You will gain an understanding of what these technologies can and cannot do, where these technologies are heading, and what the extent of their impact on our society may be.
The use of AI has been rapidly increasing in the past years, and AI is now everywhere. The amount of digital data available has helped AI techniques evolve into the age of deep learning and large models. For many years, AI has found many applications in cyber security such as intrusion detection and spam detection. More recently, how to make AI systems securer, privacy-friendly and trustworthy has become an important topic.
Do you want to understand how different AI architectures and models work and how they are applied to address cyber security problems and improve the security of systems and computer networks? Do you want to understand how AI models and pipelines can themselves be subject to attacks that compromise their performance, security, privacy, or trustworthiness?
Using cyber security problems and datasets as examples, the module will equip you with the necessary knowledge and hands-on skills about machine learning and deep learning algorithms, models and architectures, how to apply them in real-world applications, and how to interpret results from AI models. In addition, the module also covers the aspects of secure and trustworthy AI in terms of threat models, attacks on AI models and defences against them.
Software is everywhere, and its development should be tailored according to its requirements. This module will cover principles of software engineering following agile principles for guiding its development. You will investigate software modelling as means to understand and manage software complexity. As an integral part of software development, you will learn principles of planning, cost and time estimation, quality, and risk evaluation. You will also learn why software should be developed considering social, professional, and ethical principles, including security and privacy principles. You will work with your peers to develop or evolve a software system. You will apply the principles of agile methodology in your project, manage your team effectively, organise your code using version control, and resolve problems via issue tracking. You will identify risks for software projects and follow the principles for developing software with the highest professional standards.
We will give you the statistical and computing skills you need to succeed in the rest of the course. Even if you have limited mathematical skills or no computer programming knowledge we will guide you to a level where you can apply advanced data science methods effectively. This module includes subjects such as introductory probability where you’ll learn how likely you are to win at a game of cards; introductory statistics such as testing a hypothesis in a clinical trial; and programming skills in a language such as R, including data visualisation. We will then move on to more advanced topics such as linear regression, which allows you to make predictions using multiple variables, and skills that will increase your employability, such as report writing, production of slides using appropriate software, and presentation skills. You will also find out about the important ethical implications of working as a data scientist.
Assessment is through a mixture of written examinations and coursework, the relative weights of which vary according to the nature of the module. The final project is assessed by a dissertation.
For course aims and learning outcomes please see the course specification.
The School of Computing has a large range of equipment providing both UNIX (TM) and PC-based systems and a cluster facility consisting of 30 Linux-based PCs for parallel computation. New resources include a multi-core enterprise server with 128 hardware threads and a virtual machine server that supports computer security experiments.
All students benefit from a well-stocked library, giving access to e-books and online journals as well as books, and a high bandwidth internet gateway. The School and its research groups hold a series of regular seminars presented by staff as well as by visiting speakers and our students are welcome to attend.
The School of Computing has a makerspace which offers exciting new teaching and collaboration opportunities. Among other equipment, it contains milling machines, a 3D printer, laser cutter and extensive space for building and making digital artefacts.
Our taught postgraduate students enjoy a high level of access to academic staff and have their own dedicated laboratory and study room. Students whose course includes an industrial placement are supported by a dedicated team which helps them gain a suitable position and provides support throughout the placement.
Staff and research students publish regularly and widely in journals, conference proceedings and books. Among others, they have recently contributed to: Journal of Artificial Evolution and Applications; International Journal of Computer and Telecommunications Networking; Journal of Visual Languages and Computing; Journal in Computer Virology.
Strong links with industry underpin all our work, notably with Cisco, Microsoft, Oracle, IBM, Agilent Technologies, Erlang Solutions, Hewlett Packard Laboratories, Ericsson and Nexor.
All students registered for a taught Master's programme are eligible to apply for a place on our Global Skills Award Programme. The programme is designed to broaden your understanding of global issues and current affairs as well as to develop personal skills which will enhance your employability.
Our graduates have gone on to work in:
Recent graduates have gone on to develop successful careers at leading companies such as:
The University has a friendly Careers and Employability Service, which can give you advice on how to:
You have access to a dedicated Employability Coordinator who is a useful contact for all student employability queries.
If you start your course in September, you can gain practical work experience as part of your degree through our year in industry scheme - we have a dedicated Placement Team who can give advice and guidance. All our placements are in paid roles.
In previous years, students have worked at a wide range of large and small organisations, including well-known names such as:
You can take your work placement abroad. Previous destinations include Hong Kong and the US.
A year in industry gives you invaluable workplace experience, which greatly enhances your employment prospects and also helps put your academic learning into a real-world context.
The 2025/26 annual tuition fees for this course are:
For details of when and how to pay fees and charges, please see our Student Finance Guide.
Tuition fees may be increased in the second and subsequent years of your course. Detailed information on possible future increases in tuition fees is contained in the Tuition Fees Increase Policy. If you are uncertain about your fee status please contact information@kent.ac.uk.
The University will assess your fee status as part of the application process. If you are uncertain about your fee status you may wish to seek advice from UKCISA before applying.
For details of when and how to pay fees and charges, please see our Student Finance Guide.
Tuition fees may be increased in the second and subsequent years of your course. Detailed information on possible future increases in tuition fees is contained in the Tuition Fees Increase Policy. If you are uncertain about your fee status please contact information@kent.ac.uk.
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We have a range of subject-specific awards and scholarships for academic, sporting and musical achievement, plus International scholarships up to £5,000.
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Learn more about the application process or begin your application by clicking on a link below.
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