You will engage in a substantial piece of individual research and/or product development work, focused on a topic relevant to your specific discipline. The topic may be drawn from a variety of sources including: Anglia Ruskin research groups, previous/current work experience, the company in which you are currently employed, an Anglia Ruskin lecturer suggested topic or a professional subject of their specific interest (if suitable supervision is available).
View the full module definitionProfessional Issues: Computing and Society aims to provide you an understanding of the issues, opportunities and problems which have arisen as a result of the computerisation of wide areas of human activity. It is designed to enhance advanced computer reflective thinking in both computer science specialists and others, and is a key part of the programme of professional development for computer scientists and others seeking to embody professional values and approaches in the IT and computing fields. You will be covered by relevant and current topics in Computer Law (e.g. Data Protection; Intellectual Property Law; Computer Misuse) and other social, ethical and legal topics such as considering the causes and effects of systems failures (including but not limited to computer systems failure). Other aspects such as the ethical and professional responsibilities of graduates - particularly those from IT and computing disciplines - will be critically appraised. It is essential to ensure that a professional engineer has an in depth understanding of professional ethics, law and the impact of what they do on society. The knowledge and understanding obtained in this module will prepare you with an in-depth understanding on different legal, ethical, professional and system aspects of your future career particularly in the areas of IT, computer science and engineering.
View the full module definitionArtificial Intelligence (AI) covers a broad range of disciplines ranging from cognitive science and philosophy to more pragmatic engineering subjects. You will learn through specific examples how AI takes its inspiration from human and other biological behaviour that exhibit intelligence, such as problem solving, planning, decision making and optimization. Whilst intended only to provide a broad overview of AI you you will learn about all about the main areas of AI such as behaviour, genetic algorithms, neural networks, fuzzy logic and other topics. The course is intended to be quite practical and you will be expected to solve small coding challenges associated with most of the covered topics, and develop a major AI-related programming assignment. You are expected to have some familiarity in one common high-level programming language prior to taking this module (eg C#, C++ or Java). Currently the topic of AI in the public domain is very high, driven by interest in new technological developments (e.g. autonomous vehicles, applications that can personalise your lifestyle, more meaningful responses to your internet searches) and also the growing need for business to create applications that can retrieve consumer information to target new markets (data analytics). This inevitably means a graduate who can demonstrate basic yet practical technical skills in AI as part of their course portfolio will be very employable in the IT sector.
View the full module definitionUse current industry standard tool and techniques and study the theoretical/mathematical foundations of image processing in tandem with practical work and coursework that applies this theory to modern real-world scenarios. Recent case studies have included security applications for the detection of human faces, systems for the automatic analysis of biological specimens, next-generation gesture-based interfaces, and machine vision systems for automated manufacturing. Image Processing is becoming increasingly important as computing power grows, and is used in a very diverse spectrum of computational problems, from self-driving cars, factory automation and robotics, intelligent medical diagnosis, airport security, the military, astrophysics, biometric systems (such as face, fingerprint and iris recognition), environmental monitoring, human-computer interfaces (such as gesture recognition and lip-reading systems), sport (for example, goal line technology and intelligent camera control in football), barcode and QR-code devices, law (from enhancing and interpreting criminal forensic evidence to upholding copyright law through watermarking), and in any applications that entail image manipulation and augmentation, such as Facebook Messenger, Snapchat, Instagram and many others. This module provides you with the opportunity to gain a solid understanding of the core computational processes that underlie these diverse applications, and the fundamental knowledge to apply what you have learned to new situations.
View the full module definitionSecurity Management, Operations and Analytics imparts an understanding of the underlying principles associated with security management. You'll develop an understanding of security threats and vulnerabilities within modern organisational environments, and gain an understanding of the underlying principles of risk analysis and contingency planning as applied to business systems. Consideration is also given to the need for legislative compliance. This module also focuses on the current perspective of cybersecurity analytics contrasted with the emerging trends over threat hunting and threat intelligence. The limitations of an organisations current tools used in cybersecurity will be examined especially the role and the use of SIEM in an organisations operational security management. This contributes to help you understand how organisations can better understand their cyber risks environment. The Security Management and Governance module is delivered as a mixture of theory, through a series of lectures, and practical implementation, through a series of guided laboratory exercises.
View the full module definitionCloud computing can be considered as a model to enable ubiquitous, anywhere, any time on-demand network access to a shared pool of configurable resources including networks, storage, processors, servers, applications, and services which can be rapidly provisioned in real-time and automatically. The topics you will study include virtualization, data centres, cloud resource management, cloud storage and popular cloud applications including batch and data stream processing. Your learning will cover different backend technologies to create and run efficient clouds and a study of the way clouds are used by applications to realise computing on demand. You will be involved in practical tutorials on different cloud infrastructure technologies. The knowledge and understanding you will obtain in this module will prepare you to meet the requirements for jobs such as a Cloud Engineer/Developer or a Cloud DevOps Engineer. Also, you will be able to acquire the knowledge and skills to enable you to provide consultancy services to companies who are aiming to transfer to cloud-based services and products.
View the full module definition