To introduce the learner to advanced network device configuration and dynamic routing protocols. This module will build on previous knowledge and develop themes in the secure provision of local and wide area routing and switching, Internet connectivity.

1. Identify and implement VLSM.
2. Design and implement typical routing protocols within and between Autonomous Systems using both IPv4 and IPv6.
3. Configure, test and troubleshoot Routers as part of a Local Area Network.
4. Configure, test and troubleshoot Dynamic Routing protocols.
5. Implement basic network security and analysis
6. Research available and emerging communications technologies.

The objective of this module is to provide the student writer with a detailed exposure to the general process of academic writing and to then relate this general process to the specific process of writing an academic report in the computing domain.

1. Develop a research specification which includes a research question and corresponding thesis,
2. Gather, evaluate and synthesise high quality evidence to support their thesis,
3. Plan and implement a writing strategy which is logically and rhetorically correct for the writing task
4. Critically review and revise initial drafts of the document against the research specification, againstthe conventions of academic writing and against the usual standards of grammar and style.

This module will consolidate the skills learned in this and earlier programming modules. It will enable the learner to gain extensive experience in designing, implementing, testing and refactoring a substantial data management application using techniques appropriate to a DevOps environment where appropriate. They will examine a range of Design Patterns and use them where appropriate. The module has particular emphasis on writing code that adheres to clean coding principles.

1. Design, implement, test and debug a n application that serialize s and deserialize s objects .
2. Apply automated testing and test-driven development to validate and verify the quality of their applications . 
3. R ecognize , describe, and utilize appropriate Design P atterns .
4. Read, interpret and refactor code using clean coding principles.
5. Efficiently employ version control tools to support the development of multi-version programs.  
6. Develop applications that run different threads of control.

Object oriented analysis and design is concerned with the preparation and management of the requirements specification for a software system. An industry standard modelling technique supported by CASE technology will then be employed to represent these requirements.

1. Compare alternative approaches to the systems development life cycle.
2. Design data gathering techniques as part o f requirements elicitation.
3. Identify and document requirements.
4. Appraise and evaluate UML.
5. Apply the use of CASE technology to model a system using UML.

This module will introduce the learner to the fundamentals of AI and ML, with specific focus on applying supervised and unsupervised ML learning techniques. Artificial Intelligence (AI) can be described as the simulation of human behaviour by a computer. Machine Learning (ML) is a subset of AI that provides computing systems with the ability to learn and improve through experience without explicit programming.

1. Analyse and critique Artificial Intelligence technologies.
2. Examine and appraise the benefits and challenges of Artificial Intelligence.
3. Critique the design and implementation of supervised machine learning techniques.
4. Compare and contrast supervised and unsupervised machine learning methodologies.
5. Design and develop an appropriate machine learning method to meet the requirements of a particular use case.

This subject will introduce the learners scripting with Python. Learners will design and implement object-oriented programs for handling the administration of business cases in server systems. At the end, the student will be able to create scripted programs which apply basic error handling/debugging and best practices.

1. Create scripts implementing data structures as appropriate to the business use case
2. Create objects which implement object relationships with reference to efficient code .
3. Apply basic error handling and debugging techniques
4. Devise and write threaded systems
5. Evaluate and implement best practices for scripted programs.

To make students aware of the risks and vulnerabilities using hacking frameworks and to develop a comprehensive knowledge of mitigating actions. The learner will analyse and evaluate the security of mobile applications.

1. Evaluate and recognise the need for security in all application using hacking framework.
2. Perform risk assessment based on customer data needs and develop an understanding of appropriate countermeasures .
3. Assess, develop and appreciate GDPR issues for all application types.
4. Evaluate and assess the vulnerabilities in mobile architectures and develop appropriate programmer based countermeasures.

The module will provide students with experience that closely approximates a real-world commercial project. Students will analyse, design, develop, implement and test an application. The module will also enable students to develop confidence in being able to work and contribute as part of a team.

1. Select and specify a project .
2. Produce a requirements specification to industry standards.
3. Implement the software system.
4. Demonstrate and document the software artefact.

The student will learn both the theoretical concepts underpinning vulnerabilities and also how to implement remediation strategies in a modern object oriented programming language.

1. Evaluate the issues involved in designing, developing and implementing a secure application.
2. Evaluate security vulnerabilities and propose solutions for a security-conscious environment.
3. Develop memory management techniques, evaluate problems and discuss strategies and practical solutions to these issues in a modern object oriented programming language.
4. Discuss future trends in the field of software security.

This module is designed to teach the essential skills students need to make effective contributions and to have an immediate impact on the accomplishment of projects in which they are involved. Students will learn techniques required to plan, manage and control projects

1. Compare and contrast different approaches to project management.
2. Apply risk management techniques.
3. Appraise techniques used to esti mate project cost and duration .
4. Prepare graphical representations to plan and control a project.
5. Compare and contrast team organisations and select a suitable organisation based on project characteristics .

This module will examine data analysis strategies and methods and the importance of data and business intelligence to an organisation. It will introduce the use of a statistical programming language and the evaluation of methods required to pre-process, condition and extract data prior to evaluation. Furthermore, the learner will develop an understanding of how to select and implement data analytic techniques, generate insight and interpret data visualisations.

1. Identify suitable data sources for an assigned use case and evaluate pertinence of captured data.
2. Manage datasets and evaluate content for pre-processing, conditioning and extraction.
3. Apply data analytic techniques to derive insight and value from datasets.
4. Analyse the importance of data analytics in deriving insight for business intelligence.
5. Critically appraise data analytics technologies and techniques across a broad range of use cases.
6. Apply research, information gathering, critical analysis, design and implementation techniques appropriately and effectively

JavaScript is one of the most popular programming languages used by developers and it powers the modern web. This module aims to introduce students to JavaScript language fundamentals, events, the Document Object Model and Ajax data transfer.

1. Understand the core language fundamentals
2. Create & m anipulate web content
3. Transfer and manipulate server data
4. Build a significant data driven web site using client -side and server – side technologies
5. Use a version control system

This subject will extend the learners knowledge of programming through an exploration of continuous integration, build management, automated testing. Learners will design and implement key processes to support an automated software delivery pipeline.

1. Construct software in a collaborative manner using Agile techniques most appropriate to a DevOps environment.
2. Devise an appropriate test methodology for the measurement of code under specific criterion
3. Recognize and mitigate factors which may have a negative impact on the delivery lifecycle.
4. Design and implement the processes appropriate for Release and Change Management in an agile delivery organisation

This module will give students practice in academic research with the freedom to express their personal interests in the field of computing. Students will have an opportunity to critically analyse and synthesise pertinent literature regarding their area of exploration. Students will gain an appreciation of iterative development, critique and an ability to devise a plan for practical development.

1. Appraise and evaluate emerging trends from information sources and present findings.
2. Develop and document detailed aims and objectives from preliminary research.
3. Critically analyse and evaluate pertinent literature succinctly.
4. Analyse advancements in technology with regard to their impact on research and industry.
5. Develop and document a design solution using appropriate methodologies for the field of study.
6. Develop and present a prototype of high academic and technical standard.

Software engineering is an engineering discipline which is concerned with all aspects of software production, it is concerned with theories, methods and tools for professional software development . This module builds on what learners have already covered in previous modules and teaches the discipline of software engineering. Learners will evaluate the engineering methods, processes, techniques and measurements which are part of software engineering.

1. Compare and contrast software process models and select a suitable software process model for use on a software project.
2. Evaluate quality in the software process and process improvement initiatives.
3. Appraise software quality models.
4. Establish a software measurement programme.
5. Manage software configuration for a software project.

The module will develop the learners knowledge of Computer Vision, Image Processing and Video Processing. In addition, learners will evaluate multiple Computer Vision methods, processes, techniques and measurements to gain an understanding of when each should be applied. Deep Learning frameworks such as GoogleLeNet (a pre-trained Convolutional Neural Network) will also be explored and applied to Computer Vision problems.

1. Differentiate between Image Processing and Video Processing techniques.
2. Critically a nalyse the various elements of a Computer Vision system.
3. Critique and evaluate key components required to successfully perform O bject D etection.
4. Design, develop and implement algorithms to perform Object Tracking .
5. Critically examine case studies to identify a Computer Vision problem and design a suitable solution.
6. Imp lement a Computer Vision system to create meaningful output suited to a particular use case.

This course will focus on creating rapid, reliable and secure Web Applications with Python using its web framework Django. Previous Python knowledge is required for this course since the student needs it to code the different pieces of the Backend. This course builds on Python scripting proficiencies developed in semester 3. This course will cover key tasks in the development cycle of server-side web applications. At the end of this course, the student will be able to serve static files to add CSS/JavaScript and images to the application, implement forms to accept user input; manage database connectivity, sessions, authentication, and security; data analytics on the server, interacting with front-end libraries (bootstrap); and understanding of the Django framework and REST.

1. Apply scripting language fundamentals in website programming
2. Produce changing website content from database server static files datasets
3. Build a simple data-driven website
4. Identify and prepare for certain server-side scripting security issues (authentication).

Students should become sensitized to the ethical and social implications of the growing use of computers and will develop an understanding of the legal issues inherent in the discipline of computing.

1. Evaluate the utility of philosophical ethical theories in solving computer related ethical issues.
2. Examine what it means to be professional at work, in conduct and practice.
3. Discuss the consequences of pertinent legal and social issues on software developers and the role of relevant enforcement organisations.
4. Evaluate current computer-based threats.

This module will offer the student the opportunity to present the synthesis of their computing skills through a personally chosen and independently developed software artefact and supplementary document. Project Development will encourage independent investigation, design skills, revision and reflection on a specific area of computer science relevant to the student's course of study. The software artefact should be a direct response to a research investigation carried out in the Research in Computing with Emerging Technologies module.

In the submission of an accompanying document, it is expected the student will evidence the employment of an appropriate software design methodology, critical thinking and problem solving with regard to issues raised during development. The excellent student will synthesise material from modules they have taken over their course of study and bring this knowledge to bear on their chosen topic.

1. Evidence independent technical investigation .
2. Choose and apply an appropriate software design methodology for the development of a software artefact.
3. Evidence good software development skills such as efficient code, code commenting, code revision, extensibility, bug testing and deployment.
4. Explain development activities in a project report adhering to good academic standards.
5. Deliver a comprehensive presentation on the conception, research, design and development phases which led to their software artefact.

This module provides an understanding of context and methodology for contemporary software design.

It explains the shift from a purely functional software design model to software design as part of complex socio-technical contexts.

Students will be asked to think deeply on design solutions regarding the computer interface and how it can best be deployed to the demands of modern users and applications.

The module is structured around a contemporary design methodology suited to user focused application development. It will engage the student in user focused testing strategies and the practice of responding to those strategies. It will educate the student in communication practices that facilitate collaborative work in this domain.

The student will apply a UX design strategy to a given software interface problem in team workshops. Almost half of the module will be occupied by these workshops.

1. Identify, analyse and consider the implications of an emerging technology for the human computer interface.
2. Employ a UX methodology in the design of an application solution.
3. Make reasoned and researched design decisions so as to enhance the users understanding of the underlying conceptual model.
4. Evidence a deep understanding of the mobile context in that treatment.
5. Evidence comprehension and application of, user based testing strategies through interviews and user centred practical sessions.

This module will provide the learner with the skills required to gain an appreciation of the complexity of predictive model design and the steps required to develop a data prediction model. Students will also gain an appreciation of the importance of data visualisation for improved decision making and information interpretation.

1. Identify and evaluate logistic regression models and their suitability for an assigned use case.
2. Design a time series forecast model using previously identified datasets aligned with an assigned use case.
3. Develop and document the procedures required to build a time series model.
4. Plan and implement a time series model and evaluate its effectiveness and fit through relevant metrics.
5. Develop and present data forecasts using appropriate visualisation tools.

In the fast moving world of computing it is easy to become consumed by the latest technology and most popular applications. This module is designed to invite students to take a detached yet engaged look at core abstract concepts of computation such as different classes of automata and the languages they recognise as well as the functions they compute. This high-level vista will give students a chance to view computing from a challenging and rewarding point of view wherefrom both the opportunities and limitations of the standard computational models will be apparent. Non-standard computational models may be considered too if time allows.

1. Analyse the rules of a regular grammar and hence design a finite automaton that recognises the language of the grammar .
2. Convert a non-deterministic automaton into a deterministic equivalent.
3. Perform a reduction technique for producing minimal machines that perform a given task.
4. Contribute to the discussion surrounding decidable and undecidable problems as well feasible and infeasible computations.
5. Categorise languages and machines according to the Chomsky hierarchy .