BSc (Hons) Computer Science (Artificial Intelligence) Bachelor's degree at Keele University

This module introduces you to aspects of professionalism and ethics, communication, teamworking, and writing styles: these are also useful transferable skills in science and engineering more generally. The module provides you with important transitional skills that will be built upon in future modules and subsequent careers. The module provides guidance on enhancing employability skills, and advice on working in teams.

Mathematics underpins much of modern-day Data Science and is a quantitative language for how to discuss concepts and ideas in a formal setting. This module will introduce students to areas of Mathematics most relevant to these areas, including vectors and matrices, functions, graph theory, logic, information theory, probability and statistics, as well as a toolbox of essential mathematical techniques. Students will learn how mathematical abstractions can be used to represent real world scenarios

In the first part the module introduces the fundamental concepts underlying computer programming, together with techniques for applying these using Python. The module has a strong practical element. Examples will come from various areas of Computer Science and Data Science. You will gain skills of producing, compiling, and debugging simple programs in Python. These skills will be refined in later modules with applications in various areas of Computer Science. In the second part this module teach

You will learn fundamental concepts of computer hardware and software and achieve a foundation for other computer science modules. You will obtain an overview of computer systems, bridging theoretical concepts with practical applications and gain an understanding of the capabilities and limitations of modern IT. You will see logic design for core hardware components, the architecture of operating systems, essential features of programming languages, a selection of computing applications, hardwar

This module provides a comprehensive introduction to web technologies and databases, equipping students with the practical and analytical skills to design, develop, secure, and deploy modern web applications with robust data-driven backends. Upon completion, students will be able to apply industry-standard tools and best practices in contemporary web and database development.

This module provides an introduction to common techniques for exploring, summarising and modelling data. The module develops transferable skills through solving problems, modelling and the use of statistics to understand quantitative information. Emphasis is placed on understanding the meaning behind the data and on the importance of the correct presentation of findings.

This module integrates principles and practices from software engineering and human-computer interaction (HCI) to provide a comprehensive exploration of the processes involved in designing, developing, and evaluating interactive software systems. Students will work both individually and in teams to apply agile software development methodologies alongside user-centred design techniques, ensuring that technical functionality and usability requirements are addressed throughout the development lifec

This module will provide students with an introduction to artificial intelligence. Topics will including neural networks, deep learning, evolutionary algorithms and neuroevolution. The focus will initially be on understanding the underlying principles, structures, algorithms and capabilities of AI systems, and then on writing programs that use appropriate machine learning software libraries to pre-process data and apply AI to tasks such as text analysis, data analytics and visualisation, compute

An opportunity to pursue a personal interest in artificial intelligence, learning and applying programming and technical skills that complement and extend those taught within the curriculum, under guidance from an appropriate member of staff.

This module provides students with an introduction to computer graphics and animation; and with appropriate programming and media development skills to design and develop animated media. These topics are investigated through lectures, practicals and independent study. The module provides skills relevant to 2D and 3D computer graphics, and animation that have relevance to careers in animation, games and digital media production.

This module will expand on the range of artificial intelligence themes introduced earlier in the degree. It will allow students to explore in greater depth, selected research-led topics at the forefront of current thinking in the rapidly evolving field of AI. The module will also provide students with insights and understanding of fundamental issues relevant to data ethics, security and AI governance. Students will acquire practical data science and machine learning skills such as dataset analys

This module enables students to integrate and apply theoretical knowledge and problem-solving skills to a relatively large or complex technical, software, programming, research or business problem within the Artificial Intelligence discipline.

This module will provide students with an introduction to applied deep learning, with a focus on understanding its capabilities and writing programs that use appropriate software libraries to apply deep learning to tasks such as text analysis, computer vision, image processing and pattern recognition.

This module gives students interested in pursuing teaching or training as a career the opportunity to gain experience in the world of teaching in schools, colleges and other educational settings. You will develop skills highly valued by employers such as communication, and interpersonal skills, whilst learning to address individual needs and developing engaging teaching materials. You will be supported via a range of activities to prepare for your placement and have the choice to source your own

This module focuses on applying statistical techniques to health-related research using real-world data, highlighting the role of statistics in healthcare decision-making. It begins with a review of hypothesis testing and statistical inference, followed by key topics including epidemiology, survival analysis, clinical trials, and meta-analysis. Students will explore how statistical methods identify risk factors, evaluate treatments, and analyse patient outcomes, while learning techniques such as

Independently investigate an advanced topic in Artificial Intelligence, applying programming and technical skills to design and implement a solution or demonstration that extends knowledge beyond the taught curriculum, under academic supervision.

This module provides an advanced understanding of database techniques and the contemporary issues involved in deploying modern database systems. It aims to equip students with the knowledge and skills needed to develop secure, distributed, multi-tier web applications using current and emerging technologies. Designed with industry relevance in mind, the module focuses on practical competencies that prepare students for professional web development and database-driven application design.

In a competitive job market, practical skills and understanding workplace dynamics are crucial. This module allows you to gain hands-on experience, enhancing your employability, and the opportunity to gain valuable professional insights via a 75-hour placement. You will be supported by various activities to secure a role and can source your own placement or apply to university-sourced roles. This module offers flexibility on when and how you complete your placement, enabling you to balance your