Artificial Intelligence - BSc (Hons)

Course structure

Duration: 3 years full-time

The course structure below gives a flavour of the modules and provides details of the content of this programme. This listing is based on the current curriculum and may change year to year in response to new curriculum developments and innovation.

Stage 1

Compulsory Modules

CO320 Introduction to Object-Oriented Programming

CO322 Foundations of Computing I

CO328 Human Computer Interaction

CO323 Databases and the Web

CO520 Further Object-Oriented Programming

CO359 Programming for Artificial Intelligence

CO337 Computers and the Cloud

CO325 Foundations of Computing II

Stage 2

Compulsory Modules

CO539 Web Development

CO532 Database Systems

CO585 AI Systems Implementation

CO528 Introduction to Intelligent Systems

CO383 Problem Solving with Algorithms

CO557 Computer Systems

CO559 Software Development

CO519 Theory of Computing

Stage 3

Compulsory Modules

CO636 Cognitive Neural Networks

Students must select one of the following:

CO600 Project

CO620 Research Project

Plus a choice from a list of optional modules.

Teaching and assessment

Teaching

Within the School of Computing are authors of widely used computing textbooks. Programmes are taught by leading researchers who are experts in their fields.

Teaching is based on lectures, with practical classes and seminars, but we are also introducing more innovative ways of teaching, such as virtual learning environments and work-based tuition. Work includes group projects, case studies and computer simulations, with a large-scale project of your own choice in the final year.

Overall workload

Each stage comprises eight modules. Most modules run for a single 12-week term. Each module has two lectures and one to two hours of classes, usually making 14 formal contact hours per week and eight hours of 'homework club' drop-in sessions each term.

Academic support

We provide excellent support for you throughout your time at Kent. This includes access to web-based information systems, podcasts and web forums for students who can benefit from extra help. We use innovative teaching methodologies, including BlueJ and LEGO© Mindstorms for teaching programming.

Teaching staff

Our staff have written internationally acclaimed textbooks for learning programming, which have been translated into eight languages and are used worldwide.

Assessment

Assessment is by a combination of coursework and end-of-year examination and details are shown in the module outlines on the web. Project modules are assessed wholly by coursework.

The marks from stage one do not go towards your final degree grade, but you must pass to continue to stage two. 

Most stage two modules are assessed by coursework and end-of-year examination. Marks from stage two count towards your degree result. 

Most stage three modules are assessed by a combination of coursework and end-of-year examination. Projects are assessed by your contribution to the final project, the final report, and oral presentation and viva examination. Marks from stage three count towards your degree result.

Percentage of the course assessed by coursework

In stage three your project counts for 25% of the year's marks. 

Contact hours

For a student studying full time, each academic year of the programme will comprise 1200 learning hours which include both direct contact hours and private study hours.  The precise breakdown of hours will be subject dependent and will vary according to modules.  Please refer to the individual module details under Course Structure.

Methods of assessment will vary according to subject specialism and individual modules.  Please refer to the individual module details under Course Structure.

Programme aims

The programme aims to:

• Provide a programme that will attract and meet the needs of both those contemplating a career in computing and those motivated primarily by an intellectual interest in artificial intelligence
• Provide a sound knowledge and systematic understanding of the principles of computing
• Provide knowledge of key areas in artificial intelligence
• Provide generally applicable skills that will be of lasting value in a constantly changing field
• Offer a range of modules covering the foundations of computer science
• Offer a range of options to enable students to study selected areas of computer science and artificial intelligence in depth
• Provide teaching which is informed by current research and scholarship and which requires students to engage with aspects of work at the frontiers of knowledge
• Develop general critical, analytical and problem-solving skills that can be applied in a wide range of different applied computing settings.

Learning outcomes

Knowledge and understanding

You gain knowledge and understanding of:

• hardware: the major functional components of a computer system 
• software: programming languages and practice; tools and packages; computer applications; structuring of data and information 
• communication and interaction: basic computer communication network concepts; communication between computers and people; the control and operation of computers
• practice: problem identification and analysis; design development, testing and evaluation 
• theory: algorithm design and analysis; formal methods and description; modelling
• the philosophical and psychological principles of knowledge and cognition
• machine intelligence: systems, algorithms and applications.

Intellectual skills

You gain intellectual skills in:

• modelling: knowledge and understanding in the modelling and design of computer-based systems in a way that demonstrates comprehension of the trade-off involved in design choices
• reflection and communication: present succinctly to a range of audiences rational and reasoned arguments
• requirements: identify and analyse criteria and specifications appropriate to specific problems and plan strategies for their solution
• criteria evaluation and testing: analyse the extent to which a computer-based system meets the criteria defined for its current use and future development
• methods and tools: deploy appropriate theory, practices and tools for the specification, design, implementation, and evaluation of computer-based systems
• professional responsibility: recognize and be guided by the professional, economic, social, environmental, moral and ethical issues involved in the sustainable exploitation of computer technology
• computational thinking: demonstrate a basic analytical ability and its relevance to everyday life.

Subject-specific skills

You gain subject-specific skills in:

• design and implementation: specify, design and implement computer-based systems
• evaluation: evaluate systems in terms of general quality attributes and possible trade-offs presented within the given problem
• information management: apply the principles of effective information management, information organisation, and information retrieval skills to information of various kinds
• tools: deploy effectively the tools used for the construction and documentation of software, with particular emphasis on understanding the whole process involved in using computers to solve practical problems
• the ability to plan and manage projects to deliver computing systems within the constraints of requirements, timescale and budget
• the ability to recognise any risks and safety aspects that may be involved in the deployment of computing systems within a given context
• the ability to critically evaluate and analyse complex problems, argument and evidence, including those with incomplete information, and devise appropriate computing solutions, within the constraints of a budget
• identify and develop solutions for computational problems requiring machine intelligence.

Transferable skills

You gain transferable skills in:

• teamwork: Be able to work effectively as a member of a development team
• interaction reflection and communication: make succinct presentations to a range of audiences about technical problems and their solutions
• information technology: effective information-retrieval skills (including the use of browsers, search engines and catalogues); effective use of general IT facilities
• intellectual skills: critical thinking; making a case; numeracy and literacy; information literacy; the ability to construct well-argued and grammatically correct documents; the ability to locate and retrieve relevant ideas, and ensure these are correctly and accurately referenced and attributed
• self-management: managing one's own learning and development including time management and organisational skills
• professional development: appreciating the need for continuing professional development in recognition of the need for lifelong learning
• contextual awareness: the ability to understand and meet the needs of individuals, business and the community, and to understand how workplaces and organisations are governed
• sustainability: recognising factors in environmental and societal contexts relating to the opportunities and challenges created by computing systems across a range of human activities

Careers

Graduate destinations

Graduates who have both IT knowledge and business skills can expect excellent career prospects. Our graduates have gone on to work in:

• software engineering
• mobile applications development
• systems analysis
• consultancy
• networking
• web design and e-commerce
• finance and insurance
• commerce
• engineering
• education
• government
• healthcare. 

Recent graduates have gone on to develop successful careers at leading companies such as:

• BAE Systems
• Cisco 
• IBM
• The Walt Disney Company
• Citigroup 
• BT.

Help finding a job

The University has a friendly Careers and Employability Service, which can give you advice on how to:

• apply for jobs
• write a good CV
• perform well in interviews.

Work experience

You can also gain teaching experience by taking the Computing in the Classroom module.

Career-enhancing skills

You graduate with a solid grounding in the fundamentals of computer science and artificial intelligence and a range of professional skills, including:

• programming
• modelling
• artificial intelligence techniques
• design.

To help you appeal to employers, you also learn key transferable skills that are essential for all graduates. These include the ability to:

• think critically
• communicate your ideas and opinions
• analyse situations and troubleshoot problems
• work independently or as part of a team.

You can also gain extra skills by signing up for one of our Kent Extra activities, such as learning a language or volunteering.