This module explores the fundamental ethics and principles of artificial intelligence and understanding how it impacts on society, specifically examining the ethical, social and technical challenges posed by AI systems. As part of this module, students will develop their understanding of key ethical principles, the societal impact of AI and will evaluate how human factors can influence system design/model development and potentially perpetuate human biases. This module will also explore different governance approaches and legislative requirements for AI and will examine the diverse strategies for mitigating discrimination and bias in AI based systems.

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 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