MSc Advanced Computing *

All students will take the following four required modules:

1. Topics in Emerging Technologies
   Emerging technologies are innovations regarded as developments helping a field move forward at a competitive advantage. In this module you will look at such innovations within computing that are helping push the field to its boundaries and are contributing to the continuous rapid advancement of technologies and applications. You will have the opportunity to be exposed to the latest advances at the frontiers of computing via a series of invited talks, research activities and self-enquiry. 

2. DevOps
   Delivering value quickly, securely and reliably to customers is as vital to companies as it is to software consultancies and giant technology firms (such as Google, Microsoft, Apple and Meta). DevOps, which is an evolution of agile development approaches, has become the key industrial practice to achieving these goals.  In this module, you'll gain an understanding of how DevOps combines Development and Operations to achieve a fast flow of planned work into production, where its successful implementation means fewer problems experienced by customers and faster fixes to those problems.  

3. Managing Projects and Teams
   As you gain more experience as a computing professional, at some point, opportunities will arise to move beyond the role of a competent team player and project contributor. This can involve taking on responsibility for people becoming an engineering manager or can involve taking on leadership of a project or both. The career progression paths are sometimes known as the Manager’s Path and the Staff Engineer’s Path. Both career pathways necessitate a grasp of soft skills and people skills whether to manage staff members reporting to you or influence without authority. In this module, you'll learn how to manage and/or lead technical projects to successful outcomes including skills in estimation, scheduling, risk management and project management.

4. Masters Dissertation
   This module provides you with an opportunity to apply the knowledge and skills you have acquired so far from your course on a single significant technical project. It will require you to utilise practical, intellectual and decision-making skills in novel situations. The project will provide a mechanism for you to develop and demonstrate your autonomy and self-direction, whilst undertaking a problem-solving approach to a chosen topic. To support you with this, you will be allocated a Project Supervisor who is a member of the Technology Academic Team. You will meet with this supervisor on a regular basis.

In addition to the above modules, students are required to choose three of the below optional modules:

1. Advanced Software Engineering
   Software engineering is the systematic, disciplined and quantifiable approach to the development, operation and maintenance of software. Over time, the scale and complexity of the problems addressed by software have increased with a corresponding increase in the scale and complexity of the software solutions. In this module you'll learn how to address software engineering problems through the use of advanced techniques in requirements engineering, software architectures, designing for specific attributes, advanced coding, and new testing practices.
    
2. HCI and User Experience
   We design computer systems for the use of and by human beings. Making the use of computers, systems and software a delight rather than a nightmare requires attention to be paid to the user interface and the entire user experience. Different types of user interfaces necessitate different approaches. There is an ethical, legal and business imperative to ensure that computer solutions are accessible to all users, but accessibility has to be designed. This module will include topics such as user-centred design and UX design processes, user behaviour, usability, prototyping and accessibility.
    
3. Cloud Computing
   For many organisations, migrating applications and externally facing customer solutions to the cloud (AWS, Microsoft Azure, or Google Cloud) is part of their trajectory to controlling costs, adapting to change, and delivering services effectively and elastically with a global reach. This module explores cloud ecosystems, the drivers for cloud computing and when it is an appropriate solution. It provides practical skills in how to design and construct cloud solutions to deliver business needs. The resultant architectures will be secure (in terms of access to resources, workloads and applications), resilient (in terms of highly available, loosely coupled and/or fault-tolerant design choices), high-performing and scalable (in storage, compute, database and networking) and cost-optimised (in storage, compute, database and networking) and sustainable (energy efficient).
    
4. Cryptography and Applications
   Cryptography has always been an essential tool in the armoury of a cyber security professional, not least in its obvious use in protecting confidentiality. Over time cryptographic techniques have expanded to include applications to areas such as digital signatures, secure hashing and public key infrastructures. Thus, anybody wishing to pursue cyber security through an industrial or academic pathway will need a strong foundation in cryptographic techniques. This module will provide those foundations, with the right mix of theory and practical work to bring techniques to life. 
    
5. Cyber Detection and Forensic Investigation
   This module addresses the growing demand for skilled cyber security and digital forensics professionals. This module is designed to equip students with the necessary knowledge and practical skills to successfully detect, analyse, and respond to cyber security incidents and conduct comprehensive forensic investigations. The module recognises the challenges associated with the increasing volume and diversity of data sources involved in digital forensic investigations and teaches students how to manage and overcome these challenges. By the end of the module, students will have the knowledge and skills necessary to contribute to digital forensic investigations in various contexts, including criminal investigations, civil litigation, and corporate investigations.
    
6. Network and IoT Security
   This module covers basic and advanced security concepts related to wired/wireless networks and Internet of Things (IoTs). The module is focused mainly on presenting security issues that are common to wired/wireless and IoT deployments and environments, whilst maintaining a high-level view of general security aspects. The approach taken aims at first introducing the ecosystem of network topologies with the intention of producing students who will fully understand the benefits and requirements of the IoT system design cycle, from design and validation to deployment. This module will also cover critical design considerations that have emerged with the evolution of the Internet of Things, such as cybersecurity, coexistence, compliance, and continuity. Furthermore, the module presents common defence techniques and tools used to counter different security threats. Whilst the bulk of the module is aimed at Wired/Wireless Local Area Network, Smart Home (WLAN), other protocols are examined as well.
    
7. Neural Networks and Reinforcement Learning
   This module introduces fundamentals of deep learning and how it can solve problems in many areas, such as image classification, filter design and natural language processing. Neural networks are first described and how training can be achieved with backpropagation. Various forms of deep neural networks are developed, such as multilayer perceptrons, convolutional neural networks and deep reinforcement learning. The mathematics of stochastic optimisation is used to interpret and understand the behaviour and training of these networks. Programming approaches are discussed for training and deploying neural networks.
    
8. Applied AI
   Artificial Intelligence (AI) includes many techniques for classification, analysis and prediction. This module aims to give students an appreciation of the types of application areas and problems that advanced AI techniques can enhance and optimise including artificial intelligence in business and financial applications, artificial intelligence in games, artificial intelligence in health sciences and medicine, and artificial intelligence in industrial control. These techniques also have the advantage of being “explainable AI,” more so than deep learning approaches, and some are long established techniques of “business intelligence.”
    

9. Computer Vision
   Computer vision is the field of computer science that focuses on replicating parts of the complexity of the human vision system and enabling computers to identify and process objects in images and videos in the same way that humans do. Until recently, computer vision only worked in limited capacity. Thanks to advances in artificial intelligence and innovations in deep learning and neural networks, the field has been able to take great leaps in recent years and has been able to surpass humans in some tasks related to detecting and labelling objects. This module aims to develop an understanding of methods for extracting useful information (eg 3-D structure; object size, motion, shape, location and identity, etc) from images. It will allow you to understand how to construct computer vision systems for robotics, surveillance, medical imaging, and related application areas. 

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Students that wish to meet the requirements for a specialist pathway award need to choose the following options: