Computer Science BSc (Hons)

This module explores the design and development of computer software (applications) from two perspectives:

1. The implementation of software using programming code, in a high level statically typed, object-oriented programming language, such as Java.
2. The user-centred design approach to software design, considering human factors, user experience, usability, and prototyping.

The programming aspect covers a range of topics including

• The syntax and semantics of a programming language
• Different types of data, including collections
• Control flow - conditional, iterative and recursive
• Data input and output (CLI and file based)
• Object-orientation, including class design and inheritance
• Unit testing
• Basic refactoring

The human aspect considers topics that include

• User-centred design
• Human factors
• Usability
• Accessibility
• User experience
• Low and high-fidelity prototyping
• Evaluation

This module provides a strong foundation in the key areas of computing, i.e., mathematics, modern computing systems, cybersecurity, and professional skills. It equips students with the essential knowledge needed to tackle real-world computing problems and prepare them for advanced computing studies.

The mathematical aspect covers a range of topics that include:

• Set theory
• Geometric and trigonometric problem solving
• Vectors
• Linear, quadratic, fractional, and simultaneous equations
• Matrices
• Logarithmic functions
• Simple differential equations
• Introduction to complex numbers

The computing systems considers topics that include:

• Computer architecture - Hardware, software, and peripherals
• Basic computing mathematics - Number systems, binary operations, probability
• Logic gates and Boolean Algebra
• Machine Code and Assembly Language
• Compilers and Linkers
• Data Formats
• Operating Systems and File Management

The cybersecurity component addresses areas including:

• Cybersecurity Concepts
• The Human Weakness in Cybersecurity
• Cybersecurity Vulnerabilities
• Cybersecurity Exploitation
• Cryptography and Information Security
• Cybersecurity Auditing Methods
• Cybersecurity Defensive Strategies
• Programming for Cybersecurity with Python
• Ethical Hacking and Penetration Testing Lifecycle

The professional skills aspect encompasses subjects including:

• Employment & Employability
• Curriculum Vitae
• Role of Professional Bodies
• Security Obligations, Ethics and Law
• Copyright and IPR Concepts
• Report Writing and Referencing
• Proposal and Business Plans
• Social Networks and Collaboration
• Data Collection Methods
• Reflection

This module introduces fundamental concepts in database systems, emphasising their importance in modern computing. Students will gain theoretical and practical skills in designing, implementing, and querying relational databases, while also exploring alternative database management systems (DBMS), such as NoSQL and distributed databases. Through hands-on experience with tools like SQL and exposure to NoSQL systems, students will learn to choose the right database solution for different use cases.

The aims of this module are:

• Understand the role and importance of databases in computer systems and applications.
• Explain core database concepts, including schemas, tables, keys, and relationships.
• Design normalised database schemas using Entity-Relationship (ER) modelling.
• Implement relational databases in a DBMS.
• Write SQL queries for data definition, manipulation, and retrieval.
• Compare and contrast relational databases with alternative database models such as NoSQL and distributed systems.
• Explore use cases for NoSQL databases, including document stores, key-value stores, and graph databases.
• Understand the challenges and benefits of distributed databases, including replication and scalability.
• Awareness of basic techniques for database optimisation and indexing.
• Discuss data security, privacy, and ethical considerations in database design and use.

The module focuses on the application of computer programming, and related technologies, in solving everyday problems. In this process, problems and challenges will be analysed, leading to the selection and deployment of tools and techniques in response.

As a problem-based learning strategy is employed, the syllabus of the module is fluid from occurrence-to-occurrence. However, central themes and foundational concepts that will be covered are:

• Computational thinking (decomposition, abstraction, algorithm design, pattern recognition)
• Collaborative software development
• Solution evaluation
• Project portfolios

You now have the opportunity to pick an optional module to learn a new language or build on your existing language skills as part of your degree. You can choose:

• Subsidiary Language for Beginners (choice of German, Italian or Spanish)
• French: Intermediate Language Development
• Spanish: Intermediate Language Development
• Chinese: Intermediate Language Development
• German: Communication in Practice
• French: Communication in Practice
• Spanish: Communication in Practice

This module introduces intermediate topics in algorithm design, analysis and implementation using industry standard libraries, tools and techniques. Topics include asymptotic analysis, memory management and common data structures and algorithms such as:

• Arrrays
• Linked lists
• Stacks
• Queues
• Heaps
• Binary search trees
• Hash tables
• Sorting
• Searching
• Pseudorandom number generation

Additionally we cover topics such as multithreaded software development, as well as issues regarding maintainability for larger software projects.

This module provides a critical understanding of the fundamental building blocks of computer systems with an emphasis on performance efficiency. Topics include gate-level minimization, the design of combinational and sequential circuits, and an exploration of performance metrics and techniques for enhancing microprocessor architecture.

The module also covers the below topics of computer networks. 

• Network representation and topologies
• Protocols and models
• SDLC
• Switching concepts
• Spanning Tree Protocol
• VLANs
• Wireless LAN
• Subnetting
• Routing fundamentals
• Network Virtualisation
• Cloud Fundamentals
• Quality-of-Service
• Network Security

The module introduces students to the basics of static websites - their structure (HTML), aethetics (CSS) and interactivity (JavaScript). It also introduces the kep protocol of the web (HTTP) and use of it's key verbs to make requests.

Students will be taught how websites compliant with HTML and CSS document standards, as well as being accessible, as defined by the Web Content Accessibility Guidelines (WCAG).

Students will also be introduced to various associated technolohies, such as IDEs, FTP clients and introduced to DevOps processes.

Students will then be introduced to mechanisms for developing dynamic websites through the development of server-side applications which utilise a database (i.e. full-stack development).

This module provides a comprehensive introduction to data analytics, focusing on foundational concepts and practical applications. Students will develop essential skills to analyze data, solve real-world problems, and explore the rapidly growing field of big data analytics. The key perspectives are:

• Introduction to the data analytics process, including data collection, cleaning, analysis, visualisation, and interpretation.
• Hands-on experience with data analytics tools and techniques.
• Exploring big data analytics concepts, including scalable data processing and analysis.
• Promoting ethical decision-making and effective communication in data-driven contexts.

The data analytics process covers :

• Identifying business problems and defining objectives.
• Collecting and cleaning raw data for analysis.
• Performing exploratory data analysis (EDA) to uncover patterns.
• Visualising and interpreting results to derive actionable insights.

The statistical and analytical thinking aspect includes: 

• Measures of central tendency and dispersion.
• Regression analysis and correlation.
• Data modelling and simulation.

The tools and techniques component covers:

• cleaning and preprocessing using Python or R.
• SQL for querying and managing databases.
• Data visualisation using tools like Tableau, Power BI, Matplotlib and Apache Superset
• Introduction to big data ecosystem.

The big data analytics aspect addresses:

• Scalable data storage and processing.
• Analysing large datasets with distributed systems.
• Leveraging machine learning for big data insights.
• Real-time analytics and stream processing.

The ethical and professional skills aspect encompasses:

• Ethical issues in data privacy and security.
• Effective communication of data insights through storytelling.
• Collaboration and teamwork in data projects.
• Presentation and reporting of analytics outcomes.

This is an experiential learning opportunity that incorporates, 20 teaching contact hours/lectures to prepare for the150 contract hours where L5 students can use all their skills learned to date on an actual real-world (external business) client driven project, working in teams and produce an artefact. 

Students are also expected to undertake around 30 hours of self study.

This module not only gives them enhanced skills but the opportunity to work for a real client thus giving them a valuable CV and LInkedIn entry as work experience that can contribute to their employability portfolio. 

Students will collaborate in teams and produce full client documentation alongside a reflection of their expereince and this all give some much needed contemplation of their skills to date and how to use them. 

This module provides a structured, university-level work placement for 4, 5 or 7 weeks as one continuous block / period with a placement provider (i.e. industry apprioprate sector). It is designed to enhance your professional skills in a real-world job setting.

The placement can either be organised by you or with support from university staff.

All work placements within this module must be university-level; this means:

• Undertaking high-skilled work commensurate with level 5 study (e.g. report writing, attending meetings, delivering presentations, producing spreadsheets, writing content on webpages, social media, marketing services/products etc)
• Physically placed (albeit part of it can be hybrid) within an employer setting in one continuous block / period for 4, 5 or 7 weeks for a minimum of 140-147 hours over the course of the entire work placement

Where applicable, your existing part-time employer can be approached/used as the placement provider, if the high-skilled work.

• criterion above is fulfilled for the full duration of the placement.
• All quality assurances/agreements provided by the University are adhered to, by you and the employer.

The work placement context may not necessarily, reflect your degree discipline per se, but rather, it will give you an enriched experience to enhance your professional skills in a real-world job setting.

The Level 5, 40-credit modules require a basic foundation of knowledge of your chosen language e.g. GCSE or equivalent,  a Level 4 module in the same language or equivalent previous learning. This module includes an optional placement abroad, such as an intensive course at a partner university. You can choose:

• Advanced Language Development and Global Sustainability (choice of German, French or Spanish)
• Upper Intermediate Language Development and Global Employability (choice of Chinese, French or Spanish)
• Post Beginner Language Development and Global Cultures (choice of German, Italian or Spanish)

This module introduces students to developing applications for mobile devices on a major platform such as Android or iOS. This includes mobile device specific aspects such as working with location services, SDKs and libraries, making network requests, concurrency and dealing with resource limitations.

From a programming theory and application perspective, the module will consider, working with and further developing existing code, including the refactoring process, design patterns, the SOLID principles andwill  introduce students to the fundamentals of functional programming. Students will also consider the differing features of programming languages (such as type systems)

The module offers a comprehensive exploration of design thinking and its integration with human-centred design principles and practices to realise highly usable interactive systems. By the end of the module, students will be equipped to design innovative and user-friendly digital products and services, balancing business objectives with user satisfaction. This is supported by a focus on collaboration and teamwork, ensuring that the practices and processes of the industry are reflected. Over its duration, the module will engage with topics including, but not limited to, the following:

• Human-centred design and ISO 9241-210
• Balancing business goals with user needs
• UX research
• Experience mapping
• Design thinking
• Information architecture
• Progressive enhancement
• User interface design techniques
• Defining inclusive design and accessibility
• Style-guides and specifications for developers
• Design sprints for software innovation
• User testing and evaluation

Students will undertake a large self-directed software project in a specialist topic of their choice with guidance and support from a dedicated academic supervisor.

The project will begin with an appraisal of said topic, usually through a literature review and/or a commercial assessment of viability. This will be followed by planning and creation of a practical software artefact covering an implementation lifecycle, making use of project management techniques.

Ethical issues will be explored, leading to required approval for quantitative and/or qualitative testing, with results then analysed and used to inform futher development and to draw conclusions against a hypothesis.

This module is introduces the theory and practice of network protocol design, maintenance and evalutation. We will build from first principles towards a professional, research and development approach to the subject. This will include topics such as:

• Routing
• Traffic engineering
• Distributed protocol design
• Use of discrete event simulation tools
• Evaluation and analysis of protocols
• Mobile and wireless networking
• Graph theory
• Network optimisation
• Computational complexity
• Software defined networking
• Information centric networking

The module combines relevant theoretical abstractions with essential practical networking approaches to build a strong profile of skills, abilities and knowledge for the successful student.

This module offers an in-depth exploration of artificial intelligence (AI) and its transformative role in the development of advanced software systems. It introduces key theoretical approaches and practical techniques for designing and deploying intelligent technologies, empowering you with the skills to build AI-driven solutions.

Key topics covered include:

• Introduction to Artificial Intelligence: Understanding the foundations of AI and its significance in modern software development.
• Theoretical Approaches to AI: Exploring algorithms and models that underpin intelligent systems, such as decision trees, neural networks, and reinforcement learning.
• Practical AI Implementation: Gaining hands-on experience with AI techniques, including machine learning, natural language processing, and computer vision, through coding exercises and projects.
• Designing and Deploying Intelligent Systems: Examining methods for building robust, scalable, and ethically sound AI technologies.
• AI in Various Domains: Critically evaluating how AI is applied across industries such as business, healthcare, education, law, government, and scientific research, along with the ethical and societal implications of these applications.

This module blends theory with practical application, equipping you to develop intelligent systems and critically assess their impact in a wide range of real-world contexts.

The Robotics module provides an introduction to the foundational principles of robotics, exploring the theoretical aspects that underpin the design, application, and ethical considerations of robotic systems.

You will begin by examining the fundamental question: What is a robot? This includes understanding the diverse applications of robots across industries and their role in society. The module also delves into the ethical implications of robotics, such as their impact on employment, privacy, and safety.

Key technical topics include an overview of mechatronics, which integrates mechanical, electronic, and computer engineering; sensors, which enable robots to perceive their environment; and control systems, which ensure robots can perform tasks accurately and autonomously.

The module is assessed in a practical project where you will design a simulated robot, applying the concepts learned to demonstrate your understanding of robotic systems.

The module covers a range of topics that include:

• Basic cloud computing concepts, advantages, and service delivery models.
• Identity and Access Management (IAM) for centrally managing access to cloud resources.
• Secure networking practices within the cloud environments.
• Design and implementation of highly available, and secure cloud architecture.
• Design and implementation of cloud resources such as Virtual servers, Databases, and storage solutions.
• Introduction to serverless architecture within the cloud environments.
• Application Data protection, both in transit and at rest, with in the cloud environments.
• Logging and Monitoring within the cloud.
• Incident Response Management within the cloud environments.

Recognition of the need to apply data science applications in organisations.

Establishment of correct selection and application of data science techniques (i.e. data shaping, model type selection, testing and application) in various organisational contexts. 

Application of common machine learning tools (e.g. logistic regression, non-linear model estimation, neural network) in a common development environment (e.g. R, Python, Scala) in preparation for the real world context.

Evaluation of the role of ethics in the application of data science techniques.