The module aims to provide students with an analytical and practical understanding of data structures and algorithms, including – but not limited to – classification of algorithms, tree storage mechanisms, path finding, and concurrency issues.

1. Discriminate between , and experiment with, different algorithm types such as greedy algorithms, divide-and-conquer, dynamic programming algorithms .
2. Appraise, develop and analyse fundamental graph algorithms including graph search, shortest path, and minimum spanning trees .
3. Investigate and experiment with mechanisms for tree storage and balancing .
4. Identify requirements on , and implications for, data structures that must support concurrency and/or parallelism; illustrate how those requirements are met

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

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.

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.

This module will provide the learner the knowledge about how software defined networking is changing the way communication networks are managed, maintained and secured. This course will also provide knowledge about wireless network architecture, design, protocols, and security.

1. Design, analyse and implement wireless LAN communication, protocols, and architecture.
2. Design and understand security vulnerabilities, attacks, and mitigation techniques for wireless security.
3. Appraise the challenges of adopting software-defined network over the traditional network
4. Design and implement software-defined network and centralised controller with security considerations.
5. Analyse the architecture and design requirements of a software-defined network

JavaScript frameworks facilitate website construction through the concept of component-based design. This module aims to leverage a component-based framework to assemble web applications.

1. Elevate core language skills
2. Examine the RESTful architecture
3. Investigate a component-based website framework
4. Construct reusable web site co mponent s
5. Build a significant data driven component-based website

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.

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 will explore the Data Science lifecycle utilising real-world dataset. The student will explore the tools and techniques available to clean, transform and analyse data to allow them to create a data science solution. 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. This module will introduce the learner to the fundamentals of AI and ML, with specific focus on using these techniques as part of the Data Science lifecycle.

1. Critically appraise data analysis techniques available to ingest raw data, transform, clean and manipulate this data for further analysis.
2. Examine and appraise the ethical and governance considerations associated with machine learning.
3. Compare and contrast supervised and unsupervised machine learning methodologies.
4. Analyse and critique Artificial Intelligence or Machine Learning tools and techniques.
5. Design and implement a data solution for a given set of requirements using machine learning techniques.
6. Evaluate appropriate machine learning classification, optimisation and regression problems.

This module aims to enable the student to build scalable enterprise-level web applications using a structured development platform.

1. Employ a new scripting language
2. Explore a structured development platform
3. Produce integrated components using a suite of development tools
4. Build a substantial data driven scalable website