University of Kent

MSc Artificial Intelligence

Stage 1

Compulsory modules currently include the following

• Programming for AI with Python
• Machine Learning
• Natural Language Processing
• Cognitive Robotics
• Deep Learning
• Project & Dissertation

Optional modules may include the following

• Computational Creativity and Creative AI
• Introduction to Quantum Computing & Quantum Cryptography
• Artificial Intelligence and Cyber Security
• Software Engineering
• Foundations of Data Science

Programme aims

This programme aims to:

• enhance the career prospects of graduates seeking employment in the computing/IT sector
• prepare you for research and/or professional practice at the forefront of the discipline
• develop an integrated and critically aware understanding of one or more areas of computing/IT and their applications (according to your degree title)
• develop a variety of advanced intellectual and transferable skills
• equip you with the lifelong learning skills necessary to keep abreast of future developments in the field.

Learning outcomes

Knowledge and understanding

You gain knowledge and understanding of:

• how to engineer software systems that satisfy the needs of customers, using a state-of-the-art methodology and an industrially-relevant programming language
• a broad variety of advanced topics relating to computing/IT (the specific topics will depend on the optional modules you chose and may vary from year to year in response to developments in the field, staff changes etc)
• the specification, design and implementation of software systems for a variety of platforms and across a range of application domains
• the theoretical foundations of computer science
• the architecture of computer systems including hardware components and operating systems in terms of their functionality, performance and interactions
• the specification, design and implementation of information systems using the latest database and web technologies
• professional, legal, social, cultural and ethical issues related to your chosen field of computing.

Intellectual skills

You develop intellectual skills in:

• the ability to identify, analyse and formulate criteria and specifications appropriate to a given problem
• the ability to model problems and their solutions with an awareness of any tradeoffs involved
• the ability to evaluate systems, processes or methodologies in terms of general quality attributes and possible tradeoffs
• the ability to deal with complex issues both systematically and creatively
• the ability to work with self-direction and originality in tackling and solving problems
• the ability to make sound judgements in the absence of complete data
• the ability to review a research paper or technical report critically and to present your findings to a group of peers
• the ability to plan and execute a substantial research or development-based project and to report the work in the form of a dissertation.

Subject-specific skills

You gain subject-specific skills in:

• the ability to specify, design, implement and test computer-based systems
• the ability to deploy effectively the tools used for the construction and documentation of software
• The ability to undertake practical work that explores techniques covered in the programme and to analyse and comment on the findings.

Transferable skills

You gain the following transferable skills:

• the ability to plan, work and study independently and to use relevant resources in a manner that reflects good practice
• the ability to make effective use of general IT facilities, including information retrieval skills
• time management and organisational skills, including the ability to manage your learning and development
• an appreciation of the importance of continued professional development as part of lifelong learning
• the ability to work effectively as a member of a team
• the ability to communicate technical issues clearly to specialists and non-specialists
• the ability to present ideas, arguments and results in the form of a well-structured written report
• the ability to act autonomously in planning and implementing tasks at a professional or equivalent level.

Designed for excellent futures

Our course has been created with the guidance of employers, enabling our graduates to secure well-paid jobs and begin exciting careers.

Our graduates take a variety of paths, from joining well-known companies to starting their own business. Roles include:

• Machine learning engineer/developer
• AI engineer/developer
• Data analytics specialist
• Software developer
• Computer systems engineer
• Robotics software engineer/developer

Students have secured roles at companies including BT, Citigroup, IBM, Cisco, BAE Systems, and The Walt Disney Company.

Teaching and assessment

Teaching and learning style

• Lectures: Learn more about cutting-edge themes, with experienced lecturers or guest experts
• Seminars: Discuss and explore key concepts in groups
• Practical classes: Develop practical skills by building and evaluating machine learning models and AI systems
• Research-led teaching: Staff and research students regularly publish in respected global journals

Assessments:

• Exams: Some modules feature end-of-term exams
• Coursework: Practical assignments and mini projects that help you to develop your technical skills
• Dissertation: Explore a challenging research or technical problem, develop appropriate computational solutions, and communicate your findings

Placements:

• Industry roles: We offer the option to apply for a paid placement with one of our leading industry partners such as IBM, Microsoft and Oracle

Resources and Support:

• Innovative teaching: Balancing theoretical knowledge and practical skills through lectures, practical classes, and live coding demonstrations
• Student Focus: Specialist employment support, student action groups, and events
• Modern Facilities: Our recently-redeveloped facility includes a Cognitive Robotics and Autonomous Systems Lab a dedicated makerspace, and a high-performance cluster for data analytics and machine learning projects.

Study support

Postgraduate resources

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.

Dynamic publishing culture

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 of Computer Virology.

Links with industry

Strong links with industry underpin all our work, notably with Cisco, Microsoft, Oracle, IBM, Agilent Technologies, Erlang Solutions, Hewlett Packard Laboratories, Ericsson and Nexor.