Computer Science (Artificial Intelligence) with a Year in Industry

The BSc in Computer Science with a Year in Industry (Artificial Intelligence) at the University of Kent offers students a comprehensive and practical education in the rapidly evolving field of artificial intelligence. This programme is designed to equip students with a strong foundation in computer science principles, programming skills, and AI techniques, preparing them for careers in industry, research, and academia. Throughout the course, students will explore core topics such as algorithms, data structures, software development, and computer systems, alongside specialized modules in machine learning, natural language processing, robotics, and computer vision.

A distinctive feature of this programme is the inclusion of a Year in Industry, providing invaluable real-world experience. During this year, students have the opportunity to work with leading technology companies, startups, research institutions, or other organizations, applying their academic knowledge to solve practical problems. This industrial placement not only enhances technical skills but also develops professional competencies, networking opportunities, and employability prospects upon graduation.

The programme combines rigorous theoretical learning with practical project work, encouraging innovation and problem-solving in intelligent systems. Students will engage in team projects, individual assignments, and hands-on laboratory exercises to develop their coding, analytical, and critical thinking abilities. The curriculum is regularly updated to reflect advances in artificial intelligence, ensuring that graduates are well-prepared for the future AI landscape.

Upon completion of this degree, graduates will possess a versatile skill set relevant to a broad spectrum of AI applications, including healthcare, finance, robotics, gaming, and autonomous systems. They will be capable of developing machine learning models, designing intelligent systems, and understanding ethical and societal implications of AI technologies. With the University of Kent’s strong links to industry and research, students benefit from career support, networking events, and access to cutting-edge facilities and resources.

This programme is ideal for students passionate about technology and innovation, eager to make a difference with artificial intelligence, and seeking a vocational education that combines academic excellence with practical industry experience. Whether aiming to pursue a career in industry or continue with postgraduate research, students will graduate as highly skilled, adaptable, and industry-ready professionals.

Detailed Course Facts

• GBP 9000 Year (EEA)
• GBP 14860 Year (Non-EEA)

• English

Course Content

The course structure below gives a flavour of the modules that will be available to you 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. Most programmes will require you to study a combination of compulsory and optional modules, you may also have the option to take ‘wild’ modules from other programmes offered by the University in order that you may customise your programme and explore other subject areas of interest to you or that may further enhance your employability.

Stage 1

Possible modules may include:

• CO320 - Introduction to Object-Oriented Programming

  This module provides an introduction to object-oriented software development. Software pervades many aspects of most professional fields and sciences, and an understanding of the development of software applications is useful as a basis for many disciplines. This module covers the development of simple software systems. Students will gain an understanding of the software development process, and learn to design and implement applications in a popular object-oriented programming language. Fundamentals of classes and objects are introduced, and key features of class descriptions: constructors, methods and fields. Method implementation through assignment, selection control structures, iterative control structures and other statements is introduced. Collection objects are also covered and the availability of library classes as building blocks. Throughout the course, the quality of class design and the need for a professional approach to software development is emphasized

  Credits: 15 credits (7.5 ECTS credits).

• CO321 - Introduction to Information Systems

  This module looks at the nature of information and introduces the techniques needed to build information systems.
  Information Systems: the nature of information systems, applications and implications of networks;
  Information Systems Engineering: how information systems can be built, requirements analysis and specification, aspects of UML Data representation and manipulation in XML.
  In order to understand and appreciate the role of information systems and the underlying, students participate in various practical tasks and exercises which are undertaken individually or in small groups

  Credits: 15 credits (7.5 ECTS credits).

• CO322 - Foundations of Computing I

  Mathematical reasoning underpins many aspects of computer science and this module aims to provide the skills needed for other modules on the degree programme; we are not teaching mathematics for its own sake.Topics will include algebra, reasoning and proof set theory, functions, statistics.

  Credits: 15 credits (7.5 ECTS credits).

• CO324 - Computer Systems

  14. A synopsis of the curriculum
  This module aims to provide students with an understanding of the fundamental behaviour and components (hardware and software) of a typical computer system, and how they collaborate to manage resources and provide services. The module has two strands: ‘Hardware Architecture’ and ‘Operating Systems and Networks,’ which form around 35% and 65% of the material respectively. Both strands contain material which is of general interest to computer users; quite apart from their academic value, they will be useful to anyone using any modern computer system.
  Hardware Architecture
  Data representation: Bits, bytes and words. Numeric and non-numeric data. Number representation.
  Computer architecture: Fundamental building blocks (logic gates, flip-flops, counters, registers). The fetch/execute cycle. Instruction sets and types.
  Data storage: Memory hierarchies and associated technologies. Physical and virtual memory.
  Operating Systems and Networks
  Operating systems principles. Abstractions. Processes and resources. Security. Application Program Interfaces.
  Device interfaces: Handshaking, buffering, programmed and interrupt-driven i/o. Direct Memory Access.
  File Systems: Physical structure. File and directory organisation, structure and contents. Naming hierarchies and access. Backup.
  Background and history of networking and the Internet.
  Networks and protocols: LANs and WANs, layered protocol design. The TCP/IP protocol stack; theory and practice. Connection-oriented and connectionless communication. Unicast, multicast and broadcast. Naming and addressing. Application protocols; worked examples: SMTP, HTTP).

  Credits: 15 credits (7.5 ECTS credits).

• CO325 - Foundations of Computing II

  This module follows from CO322 and aims to provide students with more understanding of the theory behind the formal underpinnings of computing. It will build upon the abstract reasoning skills introduced in CO322. Matrices, vectors, differential calculus, probability and computer arithmetic will be introduced.

  Credits: 15 credits (7.5 ECTS credits).

• CO326 - Functional Programming

  Topics covered will include:Expressions, values and types. Introduction to the Hugs system (sessions and scripts). Numbers, booleans and characters. Function definitions, case analysis (guards). Approaches to testing programs. Polymorphic types. Lists and common list processing functions. Tuples. Higher order functions and currying. List comprehensions. Pattern matching, recursive function definitions. Library functions. Algebraic data types.Propositional Logic: syntax, abstract syntax, truth tables. Predicate Logic: quantifiers, scope and renaming. Equivalences in either logic, e.g. de Morgan rules.

  Credits: 15 credits (7.5 ECTS credits).

• CO520 - Further Object-Oriented Programming

  This module builds on the foundation of object-oriented design and implementation found in module CO320 Introduction to Object-Oriented Programming to provide a deeper understanding of and facility with object-oriented program design and implementation. More advanced features of object-orientation, such as inheritance, abstract classes, nested classes, graphical-user interfaces (GUIs), exceptions, input-output are covered. These allow an application-level view of design and implementation to be explored. Throughout the module the quality of application design and the need for a professional approach to software development is emphasized.

  Credits: 15 credits (7.5 ECTS credits).

• PL302 - Introduction to Philosophy: Knowledge and Metaphysics

  This module begins with an Examination of René Descartes' Meditations on First Philosophy. These not only provide a comprehensive picture of Descartes' philosophical system but also constitute an admirable introduction to several of the fundamental problems of philosophy. The writings of contemporary philosophers will also be used in the study of these problems, notably:The Problem of Knowledge (what can I know, and how?)The Mind-Body Problem (how is my mind related to my body? Is my mind - as Descartes believed - quite distinct from my body? Or am I merely a physical organism of an especially complex type?)The Problem of Freedom and Determinism Lecture Topics will include the following:Descartes on doubt and certainty; Mind/Body Dualism; Descartes' Rationalism; Russell's Empiricism - Hume's Legacy; Idealism and Phenomenalism; Materialism and Physicalism; Determinism and The Problem of Free Will The module PL303: Introduction to Philosophy: Ethics in Spring Term is recommended as a useful complement to this module while PL305: Existentialism takes up some of the issues from a particular perspective.

  Credits: 15 credits (7.5 ECTS credits).

Stage 2

Possible modules may include:

• PL583 - Philosophy of Artificial Intelligence

  The cognitive sciences include disciplines such as psychology, linguistics, anthropology, neurology, computer sciences, artificial intelligence, and philosophy of mind. They are united in their attempt to discover the nature of cognition: what is it to be intelligent, to have the capacity for rational thought, to have the ability to form concepts? An underlying assumption of classical approaches to the cognitive sciences is the idea that intelligent creatures have ‘mental representations’ and that they manipulate these representations by rule-governed processes. This is challenged by non-classical approaches. The nature of cognitive science, A.I and the philosophical assumptions that ground traditional approaches in the cognitive sciences will be the main focus of this module. Readings will be announced at the beginning of class.
  Julia Tanney is the author of several articles, such as “How to Resist Mental Representations”, “Ryle’s Regress and the Philosophy of Cognitive Science”, and “Conceptual Analysis, Theory Construction, and Philosophical Elucidation in the Philosophy of Mind”, (re)printed in Rules, Reason, and Self-Knowledge (Cambridge, MA, Harvard University Press, 2012), which criticise the key assumption of the cognitive sciences. This is the idea that in thinking, reasoning, and deliberating, we are processing information in accordance with systematic rules. This course looks carefully at the philosophical rationale for positing “mental representations” and construing our cognitive abilities by analogy with the syntactic structures of computational devices. In the course of the module, we consider the vexed question whether machines process representations and whether they can be construed as intelligent. Both philosophy and computing students are welcome.

  Credits: 30 credits (15 ECTS credits).

• CO636 - Cognitive Neural Networks

  In this module you learn what is meant by neural networks and how to explain the mathematical equations that underlie them. You also build neural networks using state of the art simulation technology and apply these networks to the solution of problems. In addition, the module discusses examples of computation applied to neurobiology and cognitive psychology.

  Credits: 15 credits (7.5 ECTS credits).

• CO528 - Introduction to Intelligent Systems

  This module covers the basic principles of machine learning and the kinds of problems that can be solved by such techniques. You learn about the philosophy of AI, how knowledge is represented and algorithms to search state spaces. The module also provides an introduction to both machine learning and biologically inspired computation.

  Credits: 15 credits (7.5 ECTS credits).

• CO531 - Software Engineering Practice

  Software systems are typically large and complex systems that require a disciplined and professional approach to their analysis, design and implementation. We show you how to deal with problems of scale and complexity combining software engineering and traditional systems methodologies.

  Credits: 15 credits (7.5 ECTS credits).

• CO522 - Algorithms, Data structures and Complexity

  By the end of this module you will have gained: the ability to design and use linked data structures; the ability to analyse the time and space behaviour (efficiency) of algorithms; an understanding of known algorithms, in particular graph, text manipulation and geometric algorithms; an understanding of the computer representation and manipulation of numerical data along with a general appreciation of numerical calculation and approximate reasoning.

  Credits: 15 credits (7.5 ECTS credits).

• CO525 - Dynamic Web

  The World Wide Web has become one of the most significant and revolutionary technologies in its ability to deliver new forms for both business and personal communication. In order to be able to fully utilise the power of the Web a good understanding of several key technologies is required. In this module you will learn how to utilise XML to create new forms of Web based documents. You will find out how flexible Web pages can be created using stylesheets and client side scripting. You will also discover how to use server side scripting to support dynamic content and interaction with other applications

  Credits: 15 credits (7.5 ECTS credits).

• CO529 - Human Computer Interaction

  This module provides an introduction to human-computer interaction. Fundamental aspects of human physiology and psychology are introduced and key features of interaction and common interaction styles delineated. A variety of analysis and design methods are introduced (e.g. GOMS. heuristic evaluation, user-centred and contextual design techniques). Throughout the course, the quality of design and the need for a professional, integrated and user-centred approach to interface development is emphasised. Rapid and low-fidelity prototyping feature as one aspect of this.

  Credits: 15 credits (7.5 ECTS credits).

• CO534 - IT Consultancy Methods

  The principal aim of this module is effectively to equip computing students to operate as IT consultants to small businesses. The module is designed to support students who wish to work in the Kent IT Clinic http://www.cs.kent.ac.uk/students/kitc/index.html
  but will also provide students with a general appreciation of the environment of IT consultancy.
  A pervading theme is that students of this course (as well as students conducting projects for KITC) should be the primary players in developing KITC’s quality plan, ensuring that quality issues are thoroughly understood by KITC participants, and that participants have a sense of ownership of the Clinic’s procedures.

  Credits: 15 credits (7.5 ECTS credits).

• CO532 - Database Systems

  This module provides an introduction to the theory and practice of database systems. It extends the study of information systems in Stage 1 by focusing on the design, implementation and use of database systems. Topics include database management systems architecture, data modelling and database design, query languages, recent developments and future prospects.

  Credits: 15 credits (7.5 ECTS credits).

• CO526 - Distributed Systems and Networks

  This module looks at the way distributed systems are modelled to contain and control the problems that naturally arise from distribution. It introduces the major techniques used to achieve coordinated and consistent use of distributed resources, both in terms of the construction of application components and the support of system-wide features such as support for security and management. It shows, by discussing the incorporation of multimedia information, how suitable use of abstractions can assist in requirements capture and system evolution.

  Credits: 15 credits (7.5 ECTS credits).

Year in industry

There are year in industry options on all our programmes. The School of Computing’s dedicated Placement Team help you to find a placement, and support you during the year. Students go to a wide range of large or small companies including IBM and

English Language Requirements

IELTS band : 6.5 CAE score : 60(Grade C)

To study at this university, you have to speak English. We advice you to

Requirements

The University will consider applications from students offering a wide range of qualifications, typical requirements are listed below, students offering alternative qualifications should contact the Admissions Office for further advice. It is not possible to offer places to all students who meet this typical offer/minimum requirement.

Qualification

Typical offer/minimum requirement

• A level: ABB
• GCSE: Mathematics grade C
• Access to HE Diploma: The University of Kent will not necessarily make conditional offers to all access candidates but will continue to assess them on an individual basis. If an offer is made candidates will be required to obtain/pass the overall Access to Higher Education Diploma and may also be required to obtain a proportion of the total level 3 credits and/or credits in particular subjects at merit grade or above.
• International Baccalaureate: 34 points overall or 16 points at HL including Mathematics 5 at HL or SL, or Mathematics Studies 6 at SL

Work Experience

No work experience is required.

Related Scholarships*

• Academic Excellence Scholarship

  "The Academic Excellence Scholarship can provide up to a 50 % reduction in tuition per semester. These scholarships will be renewed if the student maintains superior academic performance during each semester of their 3-year Bachelor programme. The scholarship will be directly applied to the student’s tuition fees."

• Access Bursary

  Bursary for UK students all subjects where the variable tuition fee rate is payable.

• Alumni Bursary

  Alumni Bursary for UK Undergraduate students

* The scholarships shown on this page are suggestions first and foremost. They could be offered by other organisations than University of Kent.

The BSc in Computer Science with a Year in Industry at the University of Kent offers students a comprehensive education in the fundamental principles and advanced applications of computer science, with a particular focus on artificial intelligence. This program is designed to provide students with a strong theoretical foundation alongside practical skills necessary to thrive in the rapidly evolving technology sector. Throughout the course, students explore various topics including programming, algorithms, data structures, software engineering, and computer systems, with specialized modules in artificial intelligence, machine learning, and robotics. The curriculum emphasizes both academic excellence and industry relevance, incorporating project work, teamwork, and problem-solving exercises that mirror real-world challenges.

A unique feature of this program is the Year in Industry, which usually takes place after the second year of study. During this year, students secure placements in renowned technology companies, research institutions, or relevant organizations, gaining valuable professional experience and industry insights. This placement year allows students to apply their academic knowledge in practical settings, fostering skills such as project management, communication, and teamwork. It also enhances employability, as students graduate with a year’s worth of professional experience and a network of industry contacts.

The University of Kent provides robust support for placement students, including dedicated career services, placement coordinators, and partnerships with industry leaders. Students are encouraged to start their placement search early, making use of university resources such as career fairs, employer talks, and mentoring schemes. The integration of practical industry experience with academic learning ensures graduates are well-prepared for careers in artificial intelligence, software development, data analysis, or further postgraduate study.

The course is delivered through a combination of lectures, tutorials, lab sessions, and project work, with a focus on active learning and collaborative development. Assessment methods include exams, coursework, presentations, and group projects. University facilities such as computer labs, simulation software, and advanced AI research labs provide students with hands-on opportunities to experiment and innovate.

Graduates of this program have gone on to successful careers in artificial intelligence, data science, cybersecurity, software engineering, and many other fields. They also have the option to continue their studies at the postgraduate level by enrolling in Master's or PhD programs. The program’s strong industry links, comprehensive curriculum, and emphasis on practical experience position students for competitive roles in the dynamic tech industry. Overall, the Computer Science with a Year in Industry program at the University of Kent is tailored to produce versatile, skilled graduates equipped for technological challenges and innovations.