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This module introduces you to the computer science of robotics, giving you an understanding of the hardware and software principles appropriate for control and localisation of autonomous mobile robots. A significant part of the module is laboratory-based, utilising physical robotic hardware to reinforce the theoretical principles covered. You will cover a range of topics including basic behavioural control architectures, multi-source data aggregation, programming of multiple behaviours, capabilities and limitations of sensors and actuators, and filtering techniques.

You will gain knowledge and hands-on experience of design and technical development of sensor-based systems. You will learn about the human-computer interaction challenges that need to be considered when creating ubiquitous computing systems along with strategies for addressing them, so as to create effective, appropriate and compelling user experiences.

This module will expose you to a variety of research methods, providing you with good quantitative and qualitative skills. Research approaches covered include:

• laboratory evaluation
• surveys
• case studies
• action research

In addition to project management, the module introduces the research process, from examining how problems are selected, literature reviews, selection of research methods, data collection and analysis, development of theories and conclusions, to the dissemination of the research based on analysis of research papers. The module also offers an overview of ethical considerations when conducting research, and supports in identifying directions for MSc projects.

You will conduct a piece of empirical and/or theoretical research in an appropriate strand of the degree, under the supervision of a member of academic staff. Where appropriate, your project may also be conducted in conjunction with an external organisation and may involve a substantial software implementation. 

This module will provide you with an advanced knowledge of computer communications networks, using examples from all-IP core telecommunications networks to illustrate aspects of transmission coding, error control, media access, internet protocols, routing, presentation coding, services and security.

The module will describe Software Defined Networks (SDNs) and provide examples of using them to enable very large scale complex network control. It will also provide advanced knowledge of various routing and query protocols in:

• Ad Hoc Networks
• Mobile Ad Hoc Networks (MANETs)
• Vehicular Ad Hoc Networks (VANETs)
• Disconnection/Disruption/Delay Tolerant Networks (DTNs)
• impact of new networking developments, such as security risks, ethics, interception and data protection will be reflected and discussed systematically

This module covers data structures, efficient algorithms on them and ways to determine their complexity. You will study some modern algorithms that are widely used in contemporary software.

The topics covered can include:

• binary search trees (red-black trees)
• dynamic programming
• graph-algorithms (eg shortest path, maximum flows)
• amortized analysis
• priority queues (binary, leftist and Fibonacci heaps)
• string algorithms (string matching, longest common subsequence).

Among the special topics relevant to contemporary application, we can study:

• public-key cryptography (the RSA cryptosystem)
• the page-rank algorithm (from Google search)
• neural networks.

The theory is practised in labs sessions where you will learn how to implement the algorithms and data structures as functional and imperative programs (using the languages Haskell and C), and apply these to solve large instances of real-world problems. The coursework consists of the implementation of some of the data types and algorithms on them.

Providing you with an introduction to machine learning, pattern recognition, and data mining techniques, this module will enable you to consider both systems which are able to develop their own rules from trial-and-error experience to solve problems, as well as systems that find patterns in data without any supervision. In the latter case, data mining techniques will make the generation of new knowledge possible, including very big data sets. This is now fashionably termed 'big data' science.

You'll cover a range of topics including:

• machine learning foundations
• pattern recognition foundations
• artificial neural networks
• deep learning
• applications of machine learning
• data mining techniques and evaluating hypotheses

Cyber security is an essential consideration for the protection of IT-based devices, systems, networks and data, providing safeguard and reassurance to the organisations and individuals that now rely (and increasingly depend) upon them. We provide coverage of both technical and human perspectives, considering the fundamental threats and safeguards that concern both personal and workplace contexts. You will emerge with the knowledge and skills necessary to enable informed cyber security decisions spanning the technical, human and organisational dimensions of the topic.

You will gain knowledge and practical experience across a range of key cyber security topics, including foundational concepts and principles, authentication and access control, operating system security, cryptographic mechanisms and applications, security management, risk assessment, cyber-attacks and threat intelligence, network and Internet security, intrusion detection and incident response, and human aspects. You will learn about the challenges that need to be considered when designing and implementing secure systems, along with associated approaches to ensure that security is addressed in an effective and holistic manner.

This module looks at the practice of malware analysis, looking at how to analyse malicious software to understand how it works, how to identify it, and how to defeat or eliminate it.  

You will look at how to set up a safe environment in which to analyse malware, as well as exploring both static and dynamic malware analysis. Although malware takes many forms, the focus of this module will primarily be on executable binaries. This will cover object file formats and the use of tools such as debuggers, virtual machines, and disassemblers to explore them. Obfuscation and packing schemes will be discussed, along with various issues related to Windows internals.

The module is practical with encouragement to safely practice the skills you're taught.

This module involves discussing current topics relating to computer security. Each week, as individuals or as a group, you will make a presentation on an assigned topic in computer security followed by a discussion. You will meet with a member of staff to discuss and plan the form of the presentation. You'll also prepare questions for the audience and write a concise (10 page) summary of the material.

The aim of the module is to gain a deeper understanding of the important topics in computer security. You'll learn how to summarise research and present it to a peer audience. 

This module focuses on the possibilities and challenges of interaction beyond the desktop. Exploring the 'mixed reality continuum' - a spectrum of emerging computing applications that runs from virtual reality (in which a user is immersed into a computer-generated virtual world) at one extreme, to ubiquitous computing (in which digital materials appear embedded into the everyday physical world - often referred to as the 'Internet of Things') at the other. In the middle of this continuum lie augmented reality and locative media in which the digital appears to be overlaid upon the physical world in different ways.

You will gain knowledge and hands-on experience of design and development with key technologies along this continuum, including working with both ubiquitous computing based sensor systems and locative media. You will learn about the Human-Computer Interaction challenges that need to be considered when creating mixed reality applications along with strategies for addressing them, so as to create compelling and reliable user experiences.