Artificial Intelligence BSc (Hons)

Academic skills when studying away from your home country can differ due to cultural and language differences in teaching and assessment practices. This module is designed to support your transition in the use and practice of technical language and subject specific skills around assessments and teaching provision in your chosen subject. The overall aim of this module is to develop your abilities to read and study effectively for academic purposes; to develop your skills in analysing and using source material in seminars and academic writing and to develop your use and application of language and communications skills to a higher level.

The topics you will cover on the module include:

• Understanding assignment briefs and exam questions.
• Developing academic writing skills, including citation, paraphrasing, and summarising.
• Practising ‘critical reading’ and ‘critical writing’
• Planning and structuring academic assignments (e.g. essays, reports and presentations).
• Avoiding academic misconduct and gaining credit by using academic sources and referencing effectively.
• Listening skills for lectures.
• Speaking in seminar presentations.
• Presenting your ideas
• Giving discipline-related academic presentations, experiencing peer observation, and receiving formative feedback.
• Speed reading techniques.
• Developing self-reflection skills.

This module will give you an overview of typical artificial intelligence (AI) methods and the underpinning math, statistics and natural science theories. You will learn about the philosophy and underpinning concepts of AI, such as problem solving by searching, knowledge representation and reasoning, and machine learning. You will develop a good understanding around the user, professional, ethical, societal, legal, environmental and economic issues and risks surrounding the design, development, operation and maintenance of AI systems.

‘AI Methods’ will prepare you for late modules such as Machine Learning, and can be one of the key providers for the technologies required by Computing Placement in your third year and Computing Dissertation in your final year. Industrial case studies will be integrated in the module to demonstrate potential real-world applications, and its role as an enabler for many societal and environmental challenges, such as EDI and green computing.

During ‘AI methods’ you will walk through a series of typical AI approaches, making use of Northumbria’s state-of-the-art computer labs. You will also engage with several simplified industry-relevant cases as part of your research-rich learning. The assessment consists of a literature review of a sub-field of AI and a product that applies AI algorithms in your chosen sub-field to computing problems.

This module will extend your understanding of system development. You will cover the algorithms theory, implementation and processing of appropriate data structures within the context of an industry-standard approach. In particular, this module will provide the knowledge to make the application faster and scalable in terms of the time complexity and properties of key algorithms and data structures. This module will also present a practical experience of implementing a range of algorithms and program testing and how to apply them in high performance computing. This module will prepare you for a placement in your third year by providing you with the common interview questions. Employers are looking for skilled programmers who can analyse the algorithms and make the appropriate selection of data structures for the project. During this module, you will work through a series of exercises, making use of Northumbria’s state-of-the-art computer labs and digital security lab. You will also critically engage with research outputs as part of your research-rich learning. The main element in assessment (100%) will be a final code solution assignment that will bring together all your new skills and techniques.

This module will give you an essential foundation in software architecture. You will learn about the importance of making high-level design choices when developing software systems. You will learn how to model and reason about architectural design choices and to take account of multiple perspectives and concerns. You will be introduced to a range of architectural styles and to their application. You will learn about the relationship between software architecture and software quality, including security, dependability, and scalability. The module will combine ways of thinking and reasoning about software systems with practical approaches to implementation. You will learn how to use appropriate frameworks and libraries, how to use tools for managing quality and risk, and how to create interfaces between system components. As part of the work you will build a component-based system.

‘Software Architecture’ will prepare you for your final year, providing approaches that will be valuable if you develop software for your Group and Individual Projects. Employers are looking for skilled software architects who can work as individuals and as members of a team in making high-level design choices and framing technical standards. Software Architect roles are often among the highest paid in the software industry.

During ‘Software Architecture’ you will work through practical exercises, making use of Northumbria’s state-of-the-art computer labs. You will also critically engage with research outputs as part of your research-rich learning. The assessment will be a final assignment to design, implement and document a software system following architectural principles.

This module will give you a good understanding of the mathematical principles and practical implementation of computer vision systems. You will be taught the fundamental mathematics, statistics, and machine learning algorithms that allow you to build computer vision systems to gain insight into the contents of images and videos.

You will develop a computer vision system that is designed for a specific application, for example the detection and classification of speed limit signs for an autonomous car, the detection and recognition of a face for secure access systems, or the detection and classification of human activity in a video. You will follow rigorous engineering principles to build the system architecture and adopt a holistic and proportionate approach to mitigate security risks in system running. You will also be required to conduct independent learning of state-of-the-art computer vision techniques and gain the knowledge to continuously improve the system performance. Furthermore, you will need to evaluate the environmental and societal impacts of the solution you have built and recommend measures to minimise adverse outcomes.

This module is a practical hands-on application of business principles. It aims to put you – and a group of your peers - into the real-world situation of solving problems for businesses. This will include contacting the client to negotiate, agree and confirm initial project requirements and then working towards a deliverable that is acceptable to the client within the given time frame. This process requires the application and development of several key skills associated with project management and consultancy such as team organisation, working with others, planning and timekeeping. Employers are looking for students with these transferable skills who can adapt and work as individuals and as members of a team in analysing computing problems and applying effective programming solutions.

The consultancy projects vary year-on-year many technology-based and, therefore, students are expected to use and develop their own expertise in this area. At the end of the module, each group will be expected to present their findings in report format and to give a formal presentation for the benefit of the tutors and the client. The projects will be supplemented by lectures and seminars introducing the skills required for such consultancy and project management work especially during the first third of the module.

This module uses your computer programming skills to develop an understanding of the theory and practice of data visualization. Data visualization is an essential part every data scientist’s toolkit. Using a range of techniques and tools you will explore complex datasets and communicate the findings of your data analysis activities. The wide availability of dashboards, programming languages such as R and Python, and interactive literate programming environments such as Jupyter Lab and Google Colab have made data visualization a much sought-after skill.

Employers seek people who can analyse their datasets and use visualization techniques to generate rich insights into the processes and phenomena from which the datasets were generated. These insights are then used to create value for the employer by, for example, improving practice, generating new leads, identifying productivity challenges, and so forth.

You will work through a series of exercises, making use of Northumbria’s state-of-the-art computer labs to anaylse and visualize a range of datasets. You will also critically engage with research outputs as part of your research-rich learning. You will also consider how to minimise
the environmental impact of data visualization, through the use of, for example, sustainable practices in data centres and using energy-efficient hardware. Ethical issues around how data visualizations can be used will be explored.

The main assessment will be a data visualization assignment that will bring together your newly developed skills and techniques and apply them to a data analysis and visualization problem which will be written up in the form of a research article supported by the source code of your visualization solution.

This module provides a broad and practical introduction to the fundamentals of digital security and forensics. The module will foster your skills in problem solving by applying investigative skills within the strict boundaries of the law and in keeping with ethical and professional codes of practice. Increasingly, employers are looking for network and cybersecurity professionals who understand how digital forensics can support the response to cybersecurity incidents, an area of digital forensics known as digital forensics incident response (DFIR). This module will provide you with the knowledge and skills to understand this area of cyber security.

The theoretical material on digital security and forensics will be re-enforced through the analysis and discussion of case studies in seminar sessions as well as sessions on the use of security and digital forensics tools in the analysis of chosen case studies in lab-based practical sessions.

You will develop analytical and evaluative skills in the appropriate use of industry software for solving problems in a variety of DFIR environments and problem situations. The ethical responsibilities of studying digital security and forensics and the need to address personal and professional integrity will be included in the module.

You will also critically engage with research outputs as part of your research-rich learning. The main element in assessment (100%) will be a written report that will bring together all your new skills and techniques.

Artificial Intelligence (AI) is rapidly changing the role of technologies in decision making processes and transforming our everyday interactions with digital systems. Human-Centered AI approaches seek to synthesize machine intelligences with human-centered thinking to conceptualise and design intelligent systems that seek to empower people and society. This module will introduce you to Human-Centered Artificial Intelligence (HCAI), where we will explore human-centered design principles and methods to envision AI systems. This module will not provide technical exploration on machine learning, statistical analysis or data modelling – instead it focuses on human-factors in the design of AI systems, and the interactions between Humans and AI (e.g., Human-AI collaboration, human-in-the-loop decision-making, interacting with chatbots and robots).

In this module you will specifically explore how to design, develop, critique interactive AI technologies from a human-centred perspective. Indicative topics that we will cover include (but are not limited to):

• User-centred design (UCD) lifecycle
• Human-AI Interaction (including ethics, trust, interpretability, transparency, and fairness)
• Understanding users, context, and social interactions,
• Prototyping techniques for interface design: low and high fidelity

Research-rich learning is heavily embedded in this module, by engaging with the latest HCAI, HCI and AI research; and conducting your own UCD research. You will be taught by academics who have published extensively in the field of HCI and Intelligent Systems. The module is designed to give you a knowledge and understanding of how to design and critically assess the human impact of AI system; while providing practical skills to enable you to design new Human-Centered AI systems.

This module will give you an understanding of the principles, concepts and practices of IT Service Management and the associated areas of Project Management, Value Management, and Change Management. These skills are essential to the successful use of Information Technology within organisations and are highly sought after by employers.

The module builds on the foundations of computing and business developed in the first year to focus on the methods and techniques used by IT professionals to manage the organisational change resulting from the implementation and use of Information Technology and Information Systems.

This includes an understanding of best practice frameworks such as ITIL.

Larger changes require the use of Projects and so this module will also provide an introduction to Project Management practices, techniques and terminologies including Project Specification, Monitoring and Controlling, and Risk Management.

The formative exercises in the workshops will include some group work but the final summative assessment is an individual assignment applying the concepts learnt within this module to a case study.

This module will give you knowledge of the principles and practice of developing cross platform, progressive mobile web applications for location aware, networked devices, using relevant technologies, and of issues relating to their use, such as accessibility. You will learn to design, develop and test mobile web applications.

‘Mobile Computing’ will provide you with knowledge and skills that are useful for later modules such as Computing Dissertation, as well as for a placement in your third year. Employers are looking for skilled mobile web application developers who can analyse problems and apply solutions.

During ‘Mobile Computing’ you will work through a series of practical exercises, making use of Northumbria’s state-of-the-art computer labs. The assessment will involve developing a mobile web application.

This module introduces you to the exciting immersive interaction technologies of Virtual Reality (VR) and Augmented Reality (AR). VR and AR are the core of the recent flourishing Metaverse applications, and they are rapidly growing to disrupt and innovate the way we work, study, and socialise in this decade.

Through this module, you will learn about the historical and recent development of VR and AR along with an understanding of the reality-virtuality continuum that helps you navigate through the landscape of immersive interaction technologies. You will have access to the University’s state-of-the-art VR/AR hardware kits for your learning and be able to horn your skills of building creative VR/AR applications using software development toolkits (SDKs) and game engines. In the process, you will also gain the ability to evaluate VR/AR designs using a comprehensive set of criteria and critique their impacts on our society, natural environment, and business world.

VR/AR are emerging technologies that attract employers and graduate employees together from a diverse range of industries, including but not limited to software engineering, graphics programming, artistic modelling, and human-computer interaction. The VR/AR app development skills covered in this module can enhance your employability in those related fields.

As a computing and digital technology student, it is imperative for you to maintain an up to date knowledge and understanding of contemporary research and technological developments relating to this ever evolving discipline. The syllabus of this module will be shaped by current scholarly and practitioner research and technological developments relevant to computing and digital technologies. This module particularly provides you opportunities to learn about developments in Computing and Digital Technologies both theoretical and technological as you prepare for your experiential learning semester where you will be working with a range of employers who are facing contemporary organisational challenges.

Indeed, the module will help you recognise, explore and develop knowledge and skills in areas of contemporary significance as they affect the wider computing and digital technologies discipline. Potential topics covered (with a focus on their relevance towards your experiential learning) could include, for example:

• Technological developments, research and issues related with contemporary technologies such as Internet of Things (IoT), Blockchain, AI, Cloud and Immersive Technologies
• Cyber Security
• Decision Intelligence, Data Fabric and Big Data
• Contemporary social, ethical and sustainability issues.

The assessment will be a literature review (3000 words) on a contemporary topic in computing and digital technologies as agreed with your tutor.

As part of your experiential learning journey you will develop a range of digital and professional competences as outlined by the Computing Curricula 2020. Computing and Digital Technologies is a wide field in which professionals can find themselves working within a number of different roles and specialisms, each requiring specific knowledge, skills and dispositions related to the tasks they perform. This module builds on the knowledge, skills and dispositions developed so far to provide an opportunity for you to tailor the learning conducted within level 5 of your programme towards acquiring those competencies that will help you develop towards becoming a professional specialising in Computing with Technology/Computing with Cybersecurity Technology/Computing with Data Science and Big Data Technology/Computing with AI technology/Computing with IT Management.

As such this module is intended to develop your understanding of these essential digital and professional competences and your ability to recognise the need for and to enter into the process of personal and professional development. Your experiential learning during your internship or consultancy or professional practice activity will specifically enable you to develop professional competencies such as being adaptable, collaborative, inventive, meticulous, passionate, proactive, professional, purpose driven, responsible, responsive and a self -directed learner to name but a few. Additionally, you will also develop digital and technical competencies as supported through experiential learning activities. These may include but not limited to systems modelling, systems architecture, computing systems fundamentals, software development, algorithms, programming, data and information management and cyber security.

This module will support you in demonstrating an increased self-awareness and self-understanding of your existing technical, management and wider professional competence, underpinned by use of theoretical concepts and models. You will conduct self analysis of your competencies using and develop a plan You will also develop an understanding of management competence by engaging in self- and social-development processes; identifying personal and professional competence development needs; recording and evaluating their competence development and identifying continuing personal and professional competence development needs.

The module is assessed through a reflective journal in which you will present and review your competence development and implications for your future career aspirations.

This module aims to provide you with an experiential learning opportunity in a workplace setting that utilises skills and knowledge acquired during the first half of your study on the programme. Indeed the Internship module is designed to deepen your knowledge and enhance employability in your specialist field. Specifically you will develop resilience and flexibility as you adapt to a different learning environment, and gain a new perspective in comparison with your taught studies. Computing and Digital Technologies is a wide discipline in which professionals can find themselves working within a number of different roles and specialisms, each requiring a specific technical skillset. This module builds on the skills developed so far to provide an opportunity for you to tailor the learning conducted so far in your programme towards acquiring those skills that will help you develop towards becoming a professional specialising in Computing with Technology/Computing with Cybersecurity Technology/Computing with Data Science and Big Data Technology/Computing with AI technology/Computing with IT Management.
Indeed, the skills and knowledge demonstrated within this module will vary on an individual basis, dependent on the area of work experience gained through placement. It is expected, however, that this is utilised as an opportunity to develop yourself within an area that is relevant to the BSc (Hons) Computing with subject specialisms, and which is an area of priority given your planned professional development.


This is an optional module, and you will be guided about the options available by your programme and career teams during semester 2 of your level 4 studies and again in semester one of your Level 5 studies. You will confirm your option to choose either Internship or consultancy project or professional practice. working with the careers team, module academic team and your personal tutor, you will conduct a skills audit to identify internship opportunities and roles that can be undertaken within the area of your subject specialism. If you are a part time learner you may also be able to use your existing workplace. Indeed, to support securing your internship you will attend workshops throughout your degree. You will also have access to careers portal hosting a wealth of employability and careers development resources.

You will be given guidance on how to identify suitable internship opportunities. The successful internship is subject to rigorous selectin process by the relevant employer. The careers and employability team will provide guidance on CV writing, interview techniques and build an attractive employability profile. While careers and employability team will assist you to find a suitable internship for you, however this is not guaranteed.

Your Internship will vary according to your specialist pathway programme of study and the host organisation, but each Internship undertaken will meet the following general requirements:

• that you will undertake work in an organisation that will last one semester in duration;
• that you will undertake work, where appropriate or necessary for professional body requirements, which are directly relevant to your programme of study.
• that the Internship will be approved by the University

Indicative syllabus:
• On the job training and work experience dependent on your role as an internee. Some examples could include, but are not limited to:
o Cyber security, Data Analytics and Big Data, Machine Learning, AI, DevOps, Enterprise Architecture, Ethical Hacking, Networks, Business Analysis.
• Refining a personal development plan.
• Reflective frameworks for evaluation

You will be encouraged to critically engage with outside practices, and to reflect on your educational development in the context of the challenges posed by an unfamiliar social, cultural and economic environment. The assessment consists of evidenced based portfolio Report (2000 words), weighted at 70% and a Poster Presentation, weighted at 30%.

This module is designed to develop your self-guided learning skills and knowledge and develop your own professional development needs in the context of your degree in Computing and Technology with subject specialisms of your choice. Computing and Digital Technologies is a wide field in which professionals can find themselves working within a number of different roles and specialisms, each requiring a specific technical skillset. This module builds on the skills developed so far to provide an opportunity for you to tailor the learning conducted within level 5 of your programme towards acquiring those skills that will help you develop towards becoming a professional specialising in Computing with Technology/Computing with Cybersecurity Technology/Computing with Data Science and Big Data Technology/Computing with AI technology/Computing with IT Management.

This is an optional module, and you will be guided about the options available by your programme and career teams during semester 2 of your level 4 studies and again in semester one of your Level 5 studies. You will confirm your option to choose either Internship or consultancy project or professional practice. Working with the module academic team, your personal tutor, academic supervisor and careers team, you will conduct a skills analysis to identify relevant training that can be undertaken within the area of your subject specialism. This training can take a number of forms, be it:

• Technical training delivered in the form of a skills bootcamp within the class environment or
• Structured online learning or
• A mini project
• Or, another appropriate form approved by the academic team.

Following completion of the training, the acquired skills will be focused towards a specified project or business challenge.

The skills and knowledge demonstrated within this module will vary on an individual basis, dependent on the area of professional development identified for study. It is expected, however, that this is utilised as an opportunity to develop yourself within an area that is relevant to the BSc (Hons) Computing with subject specialisms, and which is an area of priority given your planned professional development.

Indicative syllabus:
• Technical training dependent on identified need. Some examples could include, but are not limited to:
o Cyber security, Data Analytics and Big Data, Machine Learning, AI, DevOps, Enterprise Architecture, Ethical Hacking, Networks, Business Analysis.
• Refining a personal development plan.
• Methodologies to support system/software development/secure development (e.g. Systems Engineering).
• Reflective frameworks for evaluation.

This module aims to provide you with an experiential learning opportunity in a workplace setting that utilises skills and knowledge acquired during the first half of your study on the programme. The Advanced Practice Group UG Consultancy Project module is designed to deepen your knowledge and enhance employability in your specialist field. You will develop resilience and flexibility as you adapt to a different learning environment and gain a new perspective in comparison with your taught studies. The module will help you develop your abilities as a problem solver with valued investigative, theoretical and practical skills to implement a work-based group consultancy project.
Through this consultancy project, you will help develop hand-on experience of working on real life project that experience is directly transferrable to be utilised to the world of work after your graduation.
Computing and Digital Technologies is a wide discipline in which professionals can find themselves working within a number of different roles and specialisms, each requiring a specific technical skillset, knowledge and behaviours. This module builds on the skills developed so far to provide an opportunity for you to tailor the learning conducted within level 5 of your programme towards acquiring those skills that will help you develop towards becoming a professional specialising in Computing with Technology/Computing with Cybersecurity Technology/Computing with Data Science and Big Data Technology/Computing with AI technology/Computing with IT Management.

This is an optional module, and you will be guided about the options available by your programme and career teams during semester 2 of your level 4 studies and again in semester one of your Level 5 studies. You will confirm your option to choose either Internship or consultancy project or professional practice. You will work as a group (3 to 5 students) on a complex technical or organisational problem or commercial opportunity for the length of a semester. Your consultancy project will align to your degree specialism. You will develop a client-oriented solution along with a management report and presentation alongside an individual literature review and a personal reflection. You will be allocated academic supervisor who will support you throughout the semester. You will have regular meetings with academic supervisor who will also organise meetings with client organisation.

The assessment for this module consists of a Group Consultancy Report (2,000 words) along with presentation weighted at 50% and an Individual Assignment (2000 words) comprising a literature review (1000 words) and Reflective Learning Statement (1000 words), weighted at 50%.

Indicative syllabus:
• The project scoping documentation will be shared to scope out the expectations of consultancy project at the start of the semester. The examples could include, but are not limited to consultancy projects in the following areas of specialism:
o Cyber security, Data Analytics and Big Data, Machine Learning, AI, DevOps, Enterprise Architecture, Ethical Hacking, Networks, Business Analysis.
• Refining a personal development plan.
• Reflective frameworks for evaluation

Assessment on the module is designed to focus on the awareness of the impact of the time spent in an external learning environment, on your knowledge and understanding of the discipline. You will be encouraged to critically engage with outside practices, and to reflect on your educational development in the context of the challenges posed by an unfamiliar social, cultural and economic environment.