BSc (Hons) Computing

All students will take the following six modules in their first year. This provides students with an understanding of a range of fundamental computing topics essential to any role in the technology sector.

1. Computing Fundamentals
   This module covers the principles of computer systems, hardware components, the essence of operating systems, and relevant computing-related mathematics. This module will provide the foundational underpinning to enable students to progress deeper into different computing specialisms, and a grasp of the history of computing, recent developments and its possible future. 

2. Introduction to Networking
   This module introduces the concepts of communications and networking. It explores the Open Systems Interconnectivity (OSI) 7-layer reference model and TCP/IP Routing Suite (the 5-layer Internet reference model). TCP/IP is the model which is most commonly deployed in the majority of modern-day networks.

3. Introduction to Web Design
   The module introduces the concepts of web design, with a focus on designing responsive websites that are targeted at mobile platforms. Students are introduced to HTML, CSS and JavaScript to provide them with an understanding of what goes into the front-end of modern websites. Using a series of case studies, students will analyse the design and layout of a range of existing sites using a number of common analysis techniques.

4. Introduction to Programming
   This module introduces students to the concepts and practice of computer programming.  It is aimed at providing students with an understanding of the fundamentals of computer programming by having them work through a range of tasks focused upon layout, structure and functionality.

5. Introduction to Cyber Security
   This module provides an understanding of why cyber security matters to businesses, to society and to individuals, coupled with knowledge of basic concepts, attack techniques, attacker types, and the core elements of cyber assurance.
    
6. Introduction to AI and Data Science
   This module provides an introduction to the artificial intelligence and data science fields, covering the history of the discipline, and exploring a variety of “classical AI” topics.

Upon completion of the above modules, students will be able to align themselves with a pathway in Cyber Security, Artificial Intelligence or Web and Mobile Development. Alternatively, students can opt for a bespoke selection of modules to create their own computing pathway.

All students will take the following four required modules in their second year:

1. Software Design, Development and Engineering
   This module focuses on all phases of the modern software engineering lifecycle and advanced software engineering topics, including critical software, secure software, formal methods and project management from the practitioner’s perspective. This will be put into practice through the requirements gathering, design, implementation and testing of an extensive project that meets the needs of a particular enterprise.

2. Relational Databases
   This module provides essential knowledge and appreciation of the role of relational database systems, including basic principles and practice of design, implementation and development for both system designers and software engineers. It will include practical exercises in Structured Query Language. 

3. Computing Research Skills, Professional Practice and Ethics
   Research skills are an essential set of capabilities in the toolkit of a professional software engineer. In this module, students will develop knowledge and understanding of the purpose, processes, methods (surveys, experiments, interviews, case studies, etc.), analysis (qualitative and quantitative), and outputs of research and will be able to apply them. This module also delves into the professional, legal and ethical standards and guidelines that inform and guide best practice in business and computing.

4. Data Structures, Algorithms and Advanced Programming
   This module focuses on data structures (e.g. linked lists, trees, heaps, hash tables, etc), algorithms (sorting, searching, dynamic programming, greedy, graph, geometric, cryptographic, string matching and compression algorithms, etc), and advanced programming techniques and other language paradigms.

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

1. Advanced Web Design
   The module builds upon the content delivered to the students in Introduction to Web Design, providing students with an advanced understanding of front-end web development and design technologies. Essential for any career in the web industry, students will utilise advanced frameworks, pre-processors and design patterns to create interactive, accessible and mobile-friendly web interfaces. Through interactive hands-on sessions, students will develop their own online portfolio of work and become familiar with the prototyping and agile development methodologies common to the web industry.

2. Advanced Web Application Development
   The module will provide students with the knowledge and skills needed to develop scalable server-side applications utilising a range of influential web technologies. Throughout the module, there is an emphasis on preparing students for the web industry by ensuring best practices are followed and industry-standard software and tools are used. Additional topics such as security, ethical hacking, APIs and encryption will also be taught to ensure students have the skills required to design and develop large-scale web infrastructures.

3. Human and System Cyber Security
   Software, networks and databases do not exist in isolation, but form part of systems. Few systems are purely technical, but are socio-technical and info-socio-technical in nature, where human beings may be central or peripheral to the system, yet be the weakest link in their security. This module introduces, in the context of cyber security, system thinking and human behaviour, and how social engineering and open-source intelligence may be used in both attack and defence of systems and individuals.

4. Data Mining and Statistics
   Data science includes many techniques for classification, analysis and prediction. This module focuses on those techniques relating to data mining and statistically driven approaches. 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”.

5. Security for Computer Networks
   This module covers basic and advanced security concepts related to wired and wireless networks, and builds upon the network knowledge previously covered in Level 4 study. Students will learn about the main challenges faced by a variety of wired and wireless environments. Further, the module presents common defence techniques and tools used to counter different security threats, and also explores some of the latest network security challenges posed by recent technology developments.

6. NoSQL Databases
   Industry, commerce and research are being transformed by the potential to capture, store, manipulate, analyse and visualise data and information on a massive scale. The advent of Big Data with its variety, velocity and volume disrupted the way we store and manage data. During this module you will learn NoSQL approaches to data modelling, database design and manipulation.

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

All students will take the following required module in their third year:

1. Project and Dissertation
   The module provides the opportunity for students to apply and develop some of the knowledge and skills acquired in their degree by engaging in a significant project in a specialist area of computing, typically software or networks. It will enable and require students to utilise practical, intellectual and decision-making skills in novel situations and develop their autonomy and self-direction. 

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

1. Strategic Cyber Security
   Cyber security is now an executive-level concern in most organisations. Cyber security specialists will be required to deliver strategic value to their organisations by ensuring security is intrinsic to system architectures by design and by default, by applying appropriate standards in risk analysis, systems modelling and policy design, and scanning the horizon of emergent threat landscapes to discern new issues.

2. Information Engineering
   This covers the full range of skills and knowledge required for “Big Data” including parallel and NoSQL databases, statistical modelling and programming, machine learning, data analytics and visualisation. These skills are essential for making sense of security-related Big Data.

3. Neural Networks and Deep Learning
   A sufficiency of inexpensive computing power, sufficiently large datasets and a number of key theoretical advances created deep learning techniques which have facilitated a wave of accuracy increases across many computational tasks (computer vision, natural language processing, speech recognition, autonomous driving, etc.), making many applications practical. Deep learning is central to modern artificial intelligence. This module explains the underlying mathematics and techniques and how to use them to achieve similar feats of computational accuracy.

4. AI and Data Science Applications
   This module provides an opportunity to explore in greater depth several areas of artificial intelligence and data science. This will include an understanding of the domain theory, typical problems faced in the domain and how these might be solved.

5. Mobile Application Development
   The module is intended to provide students with an understanding of development for mobile devices with a focus on the constraints of mobile hardware, including interface and networking. Students will learn to integrate input from hardware sensors and work with networked data and services.

6. Distributed Systems
   This module provides a systematic understanding of distributed operating systems, software services and applications in terms of their architectures, functionality and behaviour. It includes case studies on the “Internet of Things” and cloud computing as well as topics on parallel programming.

7. Cyber-Physical Security
   There has been a triple convergence of computing, communications and the physical world, leading to the creation of complex cyber-physical systems, a reliance on strong cryptography, and the need to instil security into software and cyber-physical systems in the face of an ever-evolving threat landscape.

8. Cyber Forensics and Intrusion Management
   Cyber attacks are increasing in frequency and diversity with hostile actors probing for vulnerabilities, cooperating to develop exploits, and deploying these on an industrial scale. Many organisations are essentially under continuous attack from multiple actors. Eternal vigilance through monitoring and logging is essential for reactive and proactive responses. Inevitably some attacks will be successful and effective actions are required to handle these incidents, limit breaches, and collect evidence for investigation.

9. Cyber Security: Attack and Defence
   On one hand, this provides insights into the mindset of cyber attackers, a secure understanding of the ethics and legal issues in this area, and knowledge and skills in attack technologies and techniques. On the other hand, this module provides a detailed knowledge and understanding of the techniques and tools available to a security professional, and the practical skills in selecting, evaluating, designing, implementing and deploying defences to protect vulnerable software, networks and systems.

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