Digital and Technology Solutions: Software Engineer

This module will allow you to gain experience in developing mobile web applications, and have an introduction to the tools, languages and design techniques required for building functional applications. During the module you will gain exposure to a programming language that can support native mobile application development, and you will be introduced to the Model-View-Controller (MVC) software design pattern.

You will gain the knowledge and understanding of fundamental concepts of computational theory and computational complexity. You will learn how to examine whether a given problem can be solved computationally.

This module is designed to bring together the tools and techniques covered in earlier modules dealing with industrially recognised development frameworks that incorporate prototyping. It looks at the methods of analysing a business problem and subsequently highlights the process of utilising the different software development process models, which can be applied in the realisation of a software solution. In particular it addresses the issues raised through following iterative and incremental development approaches.

In addition, the module is designed to allow students to learn to carry out research activities in a systematic and organised way and to critically evaluate and review their work and the work of others. The skills learnt within this module will prepare students to research and explore project ideas that they may work on during their final year.

This module provides you with the chance to gain further experience with another programming paradigm. You will learn how to write programs using a functional programming language, Haskell. 

Functional programming is a programming paradigm that treats computation as the evaluation of mathematical functions and avoids changing-state and mutable data. For example, building an application with Functional Programming following the model Function as a Service (FAAS) is one way of achieving a "serverless" architecture and is used when building microservices applications of cloud computing.

This module will allow the student to practice systems analysis and design techniques in order to provide a design solution to a specific problem. The content of module will include:

1. Elicitation methods
2. Task and data analysis
3. Establishment and management of requirements
4. Analysis and design documentation, e.g. use cases, sequence diagrams, conceptual models
5. Change management
6. Risk management

This aim of the module is to enable the students to gain an overall understanding of marketing and organisation management. It allows the students to fully understand the day-to-day operations, including the various functions within organisations. Students will also learn how HRM can play a significant role in organisations in the long term through learning and development. Furthermore, the module will introduce the principles, methods and tools of marketing.

Machine learning is an application of artificial intelligence that provides systems with the ability to automatically learn and improve from experience without being explicitly programmed.

This module familiarises you with some basic machine learning algorithms and techniques and their applications, as well as general questions related to analysing and handling large data sets. Several software libraries and data sets publicly available will be used to illustrate the application of these algorithms. The emphasis will be thus on machine learning algorithms and applications, with some broad explanation of the underlying principles.

This module aims to develop an understanding of the important issues relating to the development of large software projects with application of design patterns and component based architectures. The structure is based on the theme of a lifecycle model with the attainment of quality as an underlying theme. It is expected that an on-going case-study will be used to underpin the theoretical concepts and practical issues.

This module emphasises on the security requirements for enterprises in the digital world. It will take an explicit approach towards identifying the security risks for organizations in the current era and delve into a holistic approach to address/mitigate against these risks. The content of the module will include:

• Introduction to a digital enterprise
• Threats to enterprise infrastructure
• The information security process: Prevention, Detection and Response
• Authentication and Authorization for enterprise networks
• Risk Assessment
• Intrusion Detection and Response
• Security Auditing
• Backup and Disaster recovery
• Best practices for organizational security
• Emerging trends for enterprise security.

You will cover the fundamental concepts and models, algorithmic and architectural techniques, developmental principles and approaches of modern distributed systems. You will enhance your critical analysis, problem solving and technical skills in distributed systems software design and implementation.

The synoptic project is a work-based project that broadly represents the skills, knowledge and behaviours in the standard. The project will provide substantive evidence from a business-related project to demonstrate the application of skills and knowledge. The end point assessment integrates the project outcomes and presentation into the overall synoptic project assessment. It will take place over a period of around 6 months, in the final year of the programme. It is designed to assess apprentices in a consistent way, irrespective of their particular workplace. Because of the significance of the project, the employer and university should work together with the apprentice to agree a project that is achievable within the employer’s business constraints and that meets the requirements of the standard. The project should be conducted as part of the apprentice’s normal work. Employers should make suitable allowance for the project to be undertaken, both in terms of time and resources. However there are some elements such as the writing of the report, particularly in its reflective aspects, that may be undertaken outside of normal work. This should be agreed between apprentice, employer and university such that apprentices are not disadvantaged in any way from performing their job and meeting the requirements of the project. Any issues with confidentiality and/or security will also be addressed between the university, employer and apprentice, allowing for projects of business value to be undertaken using real data. The project should relate to one of the specialisms in the standard.