Computer Science BSc (Hons)
Option for Placement Year
Option for Study Abroad
Option for Placement Year
Option for Study Abroad
112 UCAS Tariff points
From a combination of acceptable Level 3 qualifications which may include: A-level, T Level, BTEC Diplomas/Extended Diplomas, Scottish and Irish Highers, Access to HE Diplomas, or the International Baccalaureate.
Find out how many points your qualifications are worth by using the UCAS Tariff calculator: www.ucas.com/ucas/tariff-calculator
Northumbria University is committed to supporting all individuals to achieve their ambitions. We have a range of schemes and alternative offers to make sure as many individuals as possible are given an opportunity to study at our University regardless of personal circumstances or background. To find out more, review our Northumbria Entry Requirement Essential Information page for further details www.northumbria.ac.uk/entryrequirementsinfo
Subject Requirements:
There are no specific subject requirements for this course.
GCSE Requirements:
Applicants will need Maths and English Language at minimum grade 4/C, or an equivalent.
Additional Requirements:
There are no additional requirements for this course.
International Qualifications:
We welcome applicants with a range of qualifications which may not match those shown above.
If you have qualifications from outside the UK, find out what you need by visiting www.northumbria.ac.uk/yourcountry
English Language Requirements:
International applicants should have a minimum overall IELTS (Academic) score of 6.0 with 5.5 in each component (or an approved equivalent*).
*The university accepts a large number of UK and International Qualifications in place of IELTS. You can find details of acceptable tests and the required grades in our English Language section: www.northumbria.ac.uk/englishqualifications
UK Fee in Year 1: £9,535
* The maximum tuition fee that we are permitted to charge for UK students is set by government. Tuition fees may increase in each subsequent academic year of your course, these are subject to government regulations and in line with inflation.
International Fee in Year 1:
ADDITIONAL COSTS
There are no Additional Costs
* At Northumbria we are strongly committed to protecting the privacy of personal data. To view the University’s Privacy Notice please click here
Module information is indicative and is reviewed annually therefore may be subject to change. Applicants will be informed if there are any changes.
KV4004 -
AI Fundamentals (Core,20 Credits)
This module will give you a foundational knowledge of machine learning (ML) and artificial intelligence (AI) concepts and related Microsoft Azure services. This module will help you demonstrate knowledge of common ML and AI workloads. In addition, ‘AI Fundamentals’ will guide you through hands-on sessions and workshops on how to implement common ML and AI workloads on MS Azure.
‘AI Fundamentals’ will prepare you for later modules, as well as for a placement in your third year. Employers look for skilled graduates with industry-recognised and technology-based certifications such as the MS Azure AI Fundamentals AI-900. Employers are seeking talented individuals who can work as members of a team in understanding, analysing, and designing AI solutions leading to sustainable growth, change and impact and applying effective, responsible and ethical AI-enabled techniques.
During ‘AI Fundamentals’, students will work through a series of workshops and exercises relying on state-of-the-art AI technologies and Cloud Computing such as MS Azure. Furthermore, students will make use of Northumbria’s state-of-the-art computer labs. Students will also critically engage with research outputs as part of their research-rich learning.
‘AI fundamentals’ lectures and workshops will help students prepare for the AI Fundamentals certification exam (AI-900). This certification can be used to prepare for other Azure role-based certifications like Azure Data Scientist Associate or Azure AI Engineer Associate which are much sought-after by recruiters.
KV4006 -
Computational Thinking (Core,20 Credits)
Thinking like a computer scientist means more than being able to program a computer. It requires solving problems at multiple levels of abstraction. Before any programming begins the solution to the problem must be understood. Using real world case studies, in this module you will develop skills to decode client’s problems developing skills of abstraction and systems design to specify solutions. A key skill employers seek is the ability to solve problems, in this module you will develop computational thinking to achieve this. Computational thinking is a range of mental tools such as algorithms, modelling, logic, generalisation, decomposition, abstraction, pattern recognition and others that reflect the full breadth of Computer Science. Computational thinking is about solving problems, designing systems and understanding human behaviour. This module will teach you to reformulate seemingly difficult problems into solvable ones by using processes such as reduction, embedding, transformation or simulation.
Computational thinking can be applied to a wide variety of subject areas beyond computing, to the sciences, the arts and business. Whether developing a start-up for the latest sustainable product or fighting for social justice you will learn to be able to apply computational thinking’s vocabulary (for example algorithm, precondition, non-determinism, etc.) to many non-digital problems. In this module you will learn not to program but to conceptualize. You will learn not by rote skill, but instead by leveraging fundamental principles, by engaging with ideas not artefacts, and by embedding learning and exploration in your experience. Computational thinking has implications for everyone, everywhere and it will be integral to your future in both digital and real-life endeavours.
During ‘Computational thinking’ 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 principal elements of assessment will be directed exercises in which you try to answer questions correctly, and a project in which you will explore and decompose a problem before trying to identify a solution.
KV4007 -
Computers & Society (Core,20 Credits)
What is a ‘good’ technology? This module will provide an introduction to the range of effects, opportunities and unintended consequences, that computing has upon society. The design decisions taking in developing technologies can have far reaching consequences across all areas of society, from big philosophical questions such as ‘can computers ever be sentient’, to shopping for groceries, and biohacking.
This module will provide a foundation in concepts such as the forms of harms which can arise from the design, development, and use of technologies, including algorithmic harms, and compounding existing inequalities. Conversely you will be familiarised with where disruption provides new opportunities and challenges society to re-evaluate the status quo. This is approached through a framing which considers broader attitudes towards technology, sustainability, what drives the development of technology for profit, and how users may stage resistance against authority/power using computers. Topics include algorithmic harms, the digital citizen and pro/anti-social behaviours, morality and ethical design, and future of a digital society.
During ‘Computers & Society’ you will engage in research-rich critical analyses of harm arising through the development of technology, learn how to develop evidence-driven arguments, and position yourself as a responsible computing professional by identifying what harms you might unintentionally contribute to, and how you might avoid or mitigate doing so.
KV4008 -
Computing Fundamentals (Core,20 Credits)
This module aims to provide you with a theoretical and practical foundation required to understand the fundamental underpinnings of a computing system. You will be introduced to the basic concepts and first principles involved in computer software, information representation and the operations and components used in computer system architectures. You will gain an understanding of the underlying theory of computation as well as the major computational and programming paradigms. To complement this theoretical underpinning, you will also study the standard von Neumann computer architecture and von Neumann machine programming.
This module will help you develop logical reasoning, computational thinking and problem-solving skills employers look for. An introductory understanding of computer architecture and assembly programming improves your career options in areas such as embedded systems. Practising and developing mathematical skills and problem-solving improves your employability and allows you to develop this area further at later stages of the programme. A broad understanding of the theoretical principles of computing allows you to extend this understanding into areas of theoretical research. It also allows you to engage with wider discussions in the computing community. The module examines current computational paradigms and principles of design of computer hardware and their environmental impact.
KV4009 -
Data Fundamentals (Core,20 Credits)
This module focuses on core data concepts, and the design, implementation and use of database systems. It introduces database systems, the tools for manipulating data in databases, and design principles that ensure data security and integrity. Topics include database management systems architecture, data modelling and database design, query languages, data preparation and cleansing techniques and security, legal and ethical issues concerning the use of databases in society. You will consider issues such as the sustainability of data, and the ethics of responsible data capture and use.
You will work with database systems and data services used in industry. The module follows some of the same topics as the MS Azure Data Fundamentals (DP-900) certification course, therefore students may wish to pursue this certification during their programme.
During ‘Data Fundamentals’ you will work through a series of exercises, making use of Northumbria’s state-of-the-art computer labs. You will also engage with research outputs as part of your research-rich learning. One assessment component (50%) will be a written report that demonstrates your understanding of ethical, legal and security related issues concerning data and databases, based on current research. The other assessment component (50%) will be a practical assessment that assesses your knowledge and skills relating to key data concepts, analysis, and techniques.
‘Data Fundamentals’ will prepare you for later modules such as ‘Data Mining’, as well as for a placement in your third year. Employers are looking for skilled graduates who have technology-based certifications such as MS Azure Data Fundamentals (DP-900) that validate their skills in analysing data and applying effective solutions to computing problems.
KV4012 -
Programming (Core,20 Credits)
During this module you will learn how to create software using a high-level programming language such as Python. You will learn to select and apply standard programming structures for appropriate situations. The module will cover the use of variables, conditions, loops, subprograms, abstraction mechanisms and structured data types. You will learn to apply your skills using a professional development library, such as Flask, to build interactive user interfaces.
You will practise solving problems by breaking them down into smaller tasks. As well as constructing software that works, you will also start to consider the quality of your code and produce software that is reliable and maintainable by working to professional standards. You will learn to test, debug and maintain software of an appropriate size and to manage your time in constructing well-structured software products. We will study one programming language in detail on this module. This course will powerfully contribute to your employability by beginning your journey into software development, a skill which many employers will test before interview. As the course develops you will get to use professional software development libraries to aid your graduate employability. You will be encouraged and supported to go beyond the essential skills in and advance your development experience.
During ‘Programming’ 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 elements of assessment are a set of programming assignments that will bring together all your new skills and techniques.
KV5001 -
Academic Language Skills for Computer and Information Sciences (Core – for International and EU students only,0 Credits)
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.
KV5001 -
Academic Language Skills for Computer and Information Sciences (Core – for International and EU students only,0 Credits)
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.
KV5031 -
Advanced Programming (Core,20 Credits)
During this module you will further develop your problem solving, programming and program design skills, introduced in previous modules. You will learn the principles, knowledge, and skills to utilise the object-oriented programming (OOP) paradigm. You will learn to use OOP concepts such as inheritance, polymorphism, encapsulation, constructors, software libraries and type safety in software projects. Using an appropriate programming language, you will design and write object-oriented programs to process files, create and apply unit tests, and build graphical user interfaces (GUIs).
By using professional interview questions we will build up skills and familiarity with the software interview process to help build up your confidence for a place in the software industry.
KV5033 -
Algorithms and Data Structures (Core,20 Credits)
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.
More informationKV5035 -
Software Architecture (Optional,20 Credits)
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.
KV5036 -
Computer Vision (Optional,20 Credits)
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.
KV5037 -
Computing Consultancy Project (Optional,20 Credits)
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.
KV5040 -
Data Visualization (Optional,20 Credits)
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.
KV5041 -
Digital Forensics Incident Response (Optional,20 Credits)
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.
KV5047 -
Human-Computer Interaction (Core,20 Credits)
This module will introduce you to Human-Computer Interaction (HCI), a field of study focusing on the interaction between humans (the users) and computers. It brings together multiple disciplines, such as computer science, the social sciences, design and human-factors engineering.
In this module you will specifically explore how to design, develop and evaluate ethically aligned interactive technologies from a human-centred perspective that embed all stakeholders in the process and accounts for a sustainable development of technology. You will also engage with underlying principles and theories from contemporary HCI research.
Indicative topics that we will cover include (but are not limited to):
• User-centred design (UCD) lifecycle
• Understanding users, context, and social interactions: Requirements capture methods, Accessibility and Inclusion,
• Understanding design: Usability heuristics and evaluation; User interface standards
• Prototyping techniques for interface design: low and high fidelity
• Evaluation methods: expert appraisal and user-led
Research-rich learning is heavily embedded in this module, by engaging with the latest HCI research and carrying out your own UCD research. You will be taught by academics who have published extensively in the field of HCI.
KV5048 -
IT Service Management (Optional,20 Credits)
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.
KV5049 -
Mobile & Web App Development (Optional,20 Credits)
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.
KV5054 -
Virtual and Augmented Reality (Optional,20 Credits)
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.
LD5007 -
Contemporary Issues in Computing and Digital Technologies (Optional,20 Credits)
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.
LD5008 -
Developing Digital and Professional Competence (Optional,20 Credits)
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.
LD5009 -
London Campus UG Internship (Optional,20 Credits)
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%.
LD5010 -
London Campus Undergraduate Professional Practice (Optional,20 Credits)
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.
LD5015 -
London Campus UG Group Consultancy Project (Optional,20 Credits)
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.
KV5007 -
Work placement year (Optional,120 Credits)
This module is designed for all standard full-time undergraduate programmes within the Faculty of Engineering and Environment to provide you with the option to take a one year work placement as part of your programme.
You will be able to use the placement experience to develop and enhance appropriate areas of your knowledge and understanding, your intellectual and professional skills, and your personal value attributes, relevant to your programme of study, as well as accreditation bodies such as BCS, IET, IMechE, RICS, CIOB and CIBSE within the appropriate working environments. Due to its overall positive impact on employability, degree classification and graduate starting salaries, the University strongly encourages you to pursue a work placement as part of your degree programme.
This module is a Pass/Fail module so does not contribute to the classification of your degree. When taken and passed, however, the Placement Year is recognised both in your transcript as a 120 credit Work Placement Module and on your degree certificate.
Your placement period will normally be full-time and must total a minimum of 40 weeks.
KV5008 -
Study abroad year (Optional,120 Credits)
This module is designed for all standard full-time undergraduate programmes within the Faculty of Engineering and Environment and provides you with the option to study abroad for one full year as part of your programme.
This is a 120 credit module which is available between Levels 5 and 6. You will undertake a year of study abroad at an approved partner University where you will have access to modules from your discipline, but taught in a different learning culture. This gives you the opportunity to broaden your overall experience of learning. The structure of study will be dependent on the partner and will be recorded for an individual student on the learning agreement signed by the host University, the student, and the home University (Northumbria).
Your study abroad year will be assessed on a pass/fail basis. It will not count towards your final degree classification but, it is recognised in your transcript as a 120 credit Study Abroad module and on your degree certificate in the format – “Degree title (with Study Abroad Year)”.
KV5001 -
Academic Language Skills for Computer and Information Sciences (Core – for International and EU students only,0 Credits)
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.
KV6010 -
Big Data (Optional,20 Credits)
This module gives you a deep understanding of the concepts, theories and foundations of Big Data, and provides you with the opportunity to develop the skills to manage massive and complex data sets – as well as to infer knowledge from data - using industry standard platforms and tools. Big data analytics is the use of advanced analytic techniques on very large, diverse data sets that might include structured, semi-structured and unstructured data, from different sources, and in different sizes from terabytes to zettabytes. The module therefore includes an introduction to the specific nature and requirements of Big Data analytics, and to emerging trends and use cases where Big Data outperforms traditional data warehouse approaches. It will include an understanding – and practical use of- contemporary open-source tools such as R, Hadoop, HDFS, MapReduce, Yarn, Spark, Storm, and Hive. The module will also cover concepts of critical data studies and provide a forum for you to investigate the continuing ethical, sustainable, environmental and societal implications of Big Data. For example, sustainable practices in Big Data analysis pipeline optimization and incorporating energy-efficient design ideas. Ethical issues around how Big Data can be used will be explored.
More informationKV6011 -
Business Intelligence (Optional,20 Credits)
This module will introduce the key elements of business intelligence and organisational decision making. Drawing on business analytics, decision science and systems thinking, you will explore how organisations are able to leverage data and information to formulate a complete understanding of complex problems and to identify and implement optimal solutions. Employers are looking for data-literate graduates with the ability to explore and solve novel business problems, and as such, this module will cover topics such as organisational process modelling, business performance management, data analytics in a business context, and the use of data visualisation as a tool for exploration and communication. You will have to the opportunity to work with others in collaborative problem-solving scenarios, to investigate how businesses can use effective decision making to achieve optimal, sustainable solutions, and to explore the ethical, legal, and societal issues present when using data-driven technologies.
More informationKV6012 -
Cloud Computing (Optional,20 Credits)
This module you will provide foundational knowledge of Cloud Computing whilst also exposing you to more complex cloud services used throughout industry. Cloud Computing allows organisations across all sectors to leverage innovation and business advantage through subscription services. Through the cloud businesses can access key technologies such as file storage, networking, virtual servers and software deployment tools. You will learn the theoretical concepts of Cloud Computing and develop practical skills for using a wide range of services commonly used within industry. The skills you acquire in this module will be applicable to digital roles in all sectors including learning how to scope out a cloud solution, understanding how to manage budgets and resources, learning how to create a virtual server to specific client requirements, and learning a range of programming skills for building and configuring cloud environments. You will also develop skills in critically interpreting current practice, for non-technical colleagues. That is, you will be able to explain the implications of adapting new technologies in relation to their cost benefits to your future colleagues or employees. The assessment will involve designing, constructing, and provisioning an appropriate Cloud Computing resource for a given scenario.
Through a number of guest lectures given by experts working in cloud delivery roles you will have an opportunity to gain insights into the kind of core cloud skills employers require. You will also critically engage with research outputs as part of your research rich learning. The assessment is made of 3 components 1) Practical demonstration of configuring cloud services for a given scenario (60%); 2) A written report (max 2000 words) which demonstrates a critical reflection of your cloud solution (40%).
KV6013 -
Computing Project (40 Credits)
This is your major final year project module where you will undertake a substantial individual practical computing project related to your programme of study. You will become knowledgeable in your chosen topic including important concepts and literature. You will use and further develop skills learnt elsewhere in your programme and acquire new skills and expertise to carry out the practical computing work. These could be technical skills such as a new programming language, experimental methods, and/or the use of statistical techniques to analyse your results. You will also acquire or further develop your professional skills including communication skills (both oral presentation and report writing), literature searching and review, research methods and design, project management and personal time management. Both the technical and professional skills developed through the project module will enhance your career and employability competencies.
You will have the freedom to choose a topic of your interest or select one provided by academic staff. Your project must include you undertaking practical work of some sort using computing/IT technology. This is most frequently achieved by the creation of an artefact as the focus for covering all or part of an implementation lifecycle. However, there are a diversity of approaches you can take. For example, you could choose to conduct a more product-focused project where the main deliverable is a product of some kind such as a piece of software, a game, a computer network, an information strategy. Or it could be a more investigative and/or research-focused project such as a digital forensics investigation, a comparison analysis of AI algorithms, a user experience investigation. Or your project could be a mix of both such as building a simulated network to investigate security vulnerabilities and mitigation schemes, creating a prototype to test the effectiveness of a digital technology. Projects based solely on literature review activity and/or user/market surveys are not acceptable. You could also work with an external enterprise client to create a product in terms of their business requirements.
KV6014 -
Computing Group Project (Core,20 Credits)
In this Module you will work in a small group of your peers to undertake a significant project related to your chosen degree programme in computing. Each Project will involve the specification, design, implementation, documentation and demonstration of a technical artefact, showing your ability to synthesise information, ideas and practices to provide a quality solution together with an evaluation of that solution. This module is intended to bring together many of the concepts and skills learned in other modules prior to this point in your studies. Each project title and scope may be self-proposed or may be selected from a list of staff-defined project proposals.
Collaboration and teamwork, the capability to work with other people, from a range of cultures, to achieve common goals, for example through group work, group projects and group presentations is a key set of understanding and skills that are highly valued by employers. This Module seeks to equip you with these very skills as well as deepen an awareness/sensitivity to diversity in terms of people and cultures. Moreover, the Module will encourage networking with peers and horizon scanning to identify opportunities to advance digital capabilities and create computing solutions that seek to create a better society. In particular the module will revisit how computing products and services increasingly impact on sustainability issues.
KV6015 -
Data Analytics (Optional,20 Credits)
This module will give you an essential foundation to focus on how to conduct statistical analysis and interpret various measures correctly. You will learn to think about the process of examining data from the “ground up”, adopting pragmatic approaches e.g., how to investigate and explore data, data structures and visualisations.
‘Data Analytics’ will prepare you for the study of the computational principles, methods, and systems for extracting and structuring knowledge from data. It will also prepare you for the application and use of those principles. For example, large data sets are now generated by almost every activity in science, society, and commerce - ranging from molecular biology to social media, from sustainable energy to health care. You will explore methods to conduct efficient and pragmatic approaches to ensure you have translational skills.
During ‘Data Analytics’ you will work through a series of exercises, making use of Northumbria’s state-of-the-art computer labs. Your learning will be research-rich by providing you opportunities to link with active research groups tackling real world problems to prepare you for life beyond Northumbria. The main element in assessment (100%) will be a final assignment that will bring together all your new skills and techniques.
KV6016 -
Data Security and Governance (Core,20 Credits)
This module is set in the context of today’s society and the organisations within. Social behaviour, often in the virtual environment, creates a range of ethical issues centering on information security and governance. In addition to exploring these social and ethical issues, legal and regulatory frameworks that have been developed in recent years to try to address these issues are examined. You will also learn about security in organisations and will be introduced to a range of common threats and countermeasures. Topics include basic definitions of terminology alongside practical and theoretical frameworks to help you identify key governance and security issues and explore potential preventative measures. You will be covering terms such as ‘governance’ and ‘security’, frameworks which include the information life cycle, regulations and guidelines relating to professional conduct, privacy and data protection,
More informationKV6018 -
Evolutionary Computation (Optional,20 Credits)
Evolutionary algorithms (EAs) are a class of optimisation techniques that are inspired by natural evolution. They are well-suited to problems for which no specific solution method exists, or where other methods perform badly, and they have been used very successfully in areas as diverse as finance, engineering, architecture and logistics. In this module, you will learn about the fundamental principles of EAs, understand how (and why) they are used, and develop your own EA for a specific problem.
EAs are used extensively in business, industry, and scientific research, and the ability to analyse a problem and develop an EA to solve it demonstrates a number of sought-after key skills.
This module is research-driven, and is taught by academics who have published extensively in the field of evolutionary computation. You will benefit from access to up-to-date knowledge, codebases and datasets.
The main component of assessment is a development assignment (70%), which will bring together the skills and techniques that you will acquire during the course of the module.
Indicative list of topics:
• Natural and artificial evolution
• Representation schemes and search operators for optimisation
• Constrained and multi-objective optimisation
• Evaluation of evolutionary algorithm performance
• Theoretical foundations
• State-of-the-art applications
KV6019 -
Experimental Design for Interactive Applications (Optional,20 Credits)
This module will extend and enhance your current understanding of human-computer interaction and UX theory/practice in support of the user experience, by investigating how people experience ubiquitous computing technologies (e.g., smart devices and wearables), both individually and in groups across a variety of contexts and domains.
’Experimental Design of Interactive Applications’ will explore key aspects of interaction design, focusing on how we can effectively understand and improve user interaction in context. Real-world examples (e.g., sourced from industry/employers/research) will be used to illustrate the importance of adopting an iterative, user-centred approach to user journey mapping and interface development which supports equality, diversity, and inclusion.
A range of experimental design methods and UX practices will be covered (e.g., task-based usability tests, usability inspection methods, lab- and field-test planning and deployment), enhancing your knowledge and understanding of relevant theory and techniques whilst helping you to develop practical and transferable skills within the UX domain. Employers are looking for computing students who understand the importance of user experience and interaction design, can work as individuals or members of a team to analyse interaction design problems in context and, can apply effective experimental design and UX techniques in order to devise effective design solutions for the user experience.
KV6021 -
Machine Learning (Optional,20 Credits)
This module will provide you with knowledge and understanding of traditional, as well as modern and advanced machine learning techniques, and theoretical foundations of the algorithms, and enable you to gain practical experiences for applying these techniques to solve problems in areas such as Natural Language Processing, Image Processing, Medical Diagnosis, Speech Recognition.
‘Machine Learning’ aims to improve your employability by enabling you to gain a broad range of skills including analytical, problem solving, creativity, conducting research by addressing legal, ethical, social issues properly.
In particular, you will cover topics such as:
• Supervised machine learning techniques and classifiers
• Unsupervised machine learning techniques, clustering
• Feature extraction (supervised and unsupervised)
• Ensemble models
• Modern and advanced models
• Application of machine learning techniques in e.g. Natural Language Processing (NLP), Image Processing, Medical Diagnosis
• Legal, ethical and social issues in your applications, and techniques for security.
KV6022 -
Robotics & Automation (Optional,20 Credits)
This module will give you a deep understanding of the implementation and programming of robot technologie as autonomous systems. You will have practical experience with using the math underlying robot programming and design, including kinematics, probability and geometry. You will be taught about the components, sensor arrays and programming frameworks that make up a modern robotic system. You will research and develop a small robot that is designed for a specific industrial application, for example a warehouse stock and material transport robot, a localisation and mapping robot or a driverless vehicle. Each implementation of a robotic system will use main control architecture, state of the art sensor fusion techniques that enable localisation, obstacle avoidance, vision algorithms, path planning or navigation. The module will also cover emergent ethical and safety issues related to robotics and automation.
More informationTo start your application, simply select the month you would like to start your course.
Our Applicant Services team will be happy to help. They can be contacted on 0191 406 0901 or by using our Contact Form.
Full time Courses are primarily delivered via on-campus face to face learning but could include elements of online learning. Most courses run as planned and as promoted on our website and via our marketing materials, but if there are any substantial changes (as determined by the Competition and Markets Authority) to a course or there is the potential that course may be withdrawn, we will notify all affected applicants as soon as possible with advice and guidance regarding their options. It is also important to be aware that optional modules listed on course pages may be subject to change depending on uptake numbers each year.
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