The main aim of this module is to provide an introduction to skills and knowledge needed for the strategic management of information technology. It begins by exploring how innovative technologies/technology trends can be identified, assessed, and incorporated into organisational strategies. In addition to benefits, legislative, security management and governance implications of emerging technologies are addressed.

The module begins with horizon scanning, where emerging technologies/technology trends are identified and their potential impacts on businesses and organisations identified. Innovation and hype cycles, innovation systems, business/IT alignment and IT strategic planning methods are introduced as mechanisms through which emerging technologies can be identified and their value to businesses analysed. The construction of business cases, and the role of the business analyst in this process are also introduced. The management implications of social, ethical and environmental impacts of new technologies are then considered. Topics here include ethics, legislation and compliance requirements, security management and an introduction to IT governance frameworks.

1. Utilise methods enabling the alignment of IT innovations with strategic business objectives.
2. Construct a business case, providing justification for the adoption of a new technology as well as identifying potential risks.
3. Identify governance implications (e.g. legislative compliance, security) of adopting innovative information technologies.
4. Describe IT governance approaches and mechanisms in areas such as compliance and security.

This subject aims to make students aware of the many areas of artificial intelligence and the tools available for AI type solutions. Identify suitable problems for AI solutions. Examine in detail and implement structures for representing knowledge. The manipulation of knowledge, especially rule based systems. Implementing some of the AI techniques that have been introduced with AI Programming Languages.

1. Demonstrate Knowledge in the foundation and general principles of Artificial Intelligence
2. Identify the types of AI solutions that can be formulated
3. Apply represenations to problem domains
4. Recognise structure and program various knowledge representations

This course will help students understand the process of developing a business start-up.

1. Discover and envision new business ideas
2. Evaluate business opportunities
3. Refine business opportunities based on research
4. Articulate business issues affecting startups

The module is intended to help students to understand the necessary skills to interpret numerical and graphical information and describe data appropriately. It will introduce some basic concepts for statistical inference and utilise computer software to interpret data. Additionally, it will introduce students to the concept of Big Data.

1. Appraise Data Analytics and the emergence of big data.

2. Analyse results from data using appropriate statistical methodology.
3. Examine and implement different hypothesis testing techniques for decision making.

4. Develop computer software for the solution of statistical problems.

The aim of this module is to provide learners with an understanding of common security vulnerabilities associated with modern software applications and the various remediation strategies associated with same. In addition to this, the module covers the usage of cryptography in application software for securing both data at rest and data in transit.

1. Analyse source code and identify the presence/absence of common security vulnerabilities.
2. Compose countermeasure solutions when faced with security vulnerabilities at the source code level.
3. Compose application security requirements as part of the Requirements Engineering and Software Design/Architecture phases of the SDLC.
4. Discuss the role of cryptography in both the secure storage and transportation of data.

The module is intended to help students understand the range of techniques deploying in Machine/Deep learning environments. It will introduce students to neural networks, training sets and how to study the input/output of a machine learning system.

1. Obtain an understanding of machine learning approaches and neural networks.
2. Examine and distinguish the areas of supervised and unsupervised machine learning.
3. Discuss the relationships between training set, test set, generalisation, cross validation.
4. Utilise data mining and appropriate machine learning techniques to solve real problems.

User Experience (UX) is used in the design of interfaces, products and services. In order to create a successful user experience, products must be intuitive, enjoyable and seamless to interact with, tying together the disciplines of graphical and interface design, industrial design, marketing, branding and engineering design. In this module students design products using research, design techniques, cognitive psychology, low and high-fidelity prototyping and testing with the emphasis on the user experience at all times.

1. Conduct user research and analyse and discuss findings
2. Justify the importance of prototyping and testing
3. Develop improved prototypes through cyclical user testing
4. Iteratively develop and modify a high-fidelity working prototype to an agreed specification

The Advanced Programming module enables the students to have a deeper understanding of programming topics such as asynchronous programming and isolated storage. The module takes a hands-on approach and encourages students to implement complex applications utilising the programming techniques mentioned above. Students will be encouraged to use their existing programming skills while learning new ways of programming such as multi-threading. Students will also be encouraged to use a variety of application types to implement their code.

1. Identify uses for and utilise BackgroudWorker components in an application.
2. Implement advanced thread processing in an application.

3. Debug multithreaded applications.
4. Identify uses for isolated storage and implement isolation in a multitude of applications.

The aim of this module is to provide learners with the skills to simulate malicious attacks against software applications from a black-hat hacker/black-box testing perspective using industry standard ethical-hacking tools.

1. Locate and analyse relevant publicly available information with regard to the software application under test.
2. Simulate attacks on a software application from a black-box perspective using industry standard ethical hacking tools.
3. Evaluate automated testing tool results with respect to business impact and false positives.
4. Compose exploits and countermeasures in response to vulnerabilities identified.

This will focus on working with database objects such as triggers, user-defined functions. It will further examine storing and manipulating non-relational data objects such as xml (producing data, schemas and schematrons), JSON and other non-relational objects such as Spatial and Hierarchical data. How to model, develop and manipulate graph tables will also be covered.

1. Design and create database triggers
2. Design and create user defined functions
3. Create and manipulate XML objects
4. Store and manipulate other non relational data objects
5. Model, create and manipulate complex data relationships using graph tables

The module Cloud Development will allow the learner to develop state-of-the-art applications for public cloud infrastructure. A brief overview of cloud development services will be provided, and the learner will the cover topics including advanced NoSQL, serverless compute, containers, microservices, caching and automation. The module will be programming-language agnostic, with an emphasis on the learner using public forums to research, raise and solve issues.

1. Describe the core services used in cloud application development

2. Employ a cloud SDK to interact with object and NoSQL storage across multiple regions

3. Describe the different use cases for, and implement, container, microservice and serverless compute solutions

4. Implement edge computing and caching

5. Utilise queues, notifications and automation to ensure application decoupling

In Project 400 students will undertake a significant piece of independent work under supervision. The module aims to encourage innovation, exploratory learning and to act as an integrating module to allow the student to draw on knowledge learned in previous years. The module exposes the student to the application of research methodologies and aims to develop critical thinking and analysis skills.

1. Develop a major project by working either individually or in a small team to a deadline involving, inter alia, planning, and coordination of design & development activities, setting realistic work objectives, and presenting and documenting the work undertaken.
2. Undertake a comprehensive review of relevant and appropriate literature to determine current knowledge in the project area.
3. Demonstrate initiative, analytical, and problem-solving skills in developing a detailed, viable methodology for addressing an open-ended problem.
4. Integrate and evaluate the relevance, strengths, and weaknesses of approaches developed throughout the programme.
5. Produce a written thesis which meets the required standards of scholarship and technical expertise.
6. Demonstrate the appropriate written and oral communication skills required of a professional practitioner.