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Designed to meet the needs of industry, MSc Advanced Computer Science will help you to build on your computing experience and develop cutting edge IT skills.

Designed to meet the needs of industry, MSc Advanced Computer Science will help you to build on your computing experience and develop cutting edge IT skills.

You will develop an in-depth understanding of the topics that are defining the industry today. Gaining advanced computer science skills in areas such as: application design, computer network security, system development, big data, and cloud computing. You will also have the opportunity to explore computational intelligence, object-oriented design, artificial intelligence, wireless computer network technology, network security, and system development.

This advanced computer science is accredited by BCS, the Chartered Institute for IT on behalf of the Engineering Council for the purposes of partially meeting the academic requirement for registration as a Chartered Engineer - and furthermore, for the purposes of fully meeting the further learning academic requirement for registration as a Chartered IT Professional.

This course will further enhance your already established skills in computer science, providing you with an advanced qualification that will be highly regarded by employers. 

Graduates will be equipped with the latest skills to excel in a variety of careers in the IT industry, such as software engineering, network design and management, artificial intelligence or IT consultancy.

As a Northumbria University student, you will have access to state-of-the-art facilities. Including the new Computer and Information Sciences building located in the heart of Newcastle, with access to dedicated IT systems on evenings and weekends. Our equipment is industry leading, meaning that you will graduate familiar with industry standard equipment. Learn more about the computer science facilities here.

Are you interested in pursuing an IT career, but don’t have an undergraduate degree in a computing-related subject? MSc Computer Science is the course you’ll need to help you change direction. 

Are you interested in pursuing an IT career, but don’t have an undergraduate degree in a computing-related subject? MSc Computer Science is the course you’ll need to help you change direction. 

Course Information

Level of Study
Postgraduate

Mode of Study
1 year full-time

Department
Computer and Information Sciences

Location
City Campus, Northumbria University

City
Newcastle

Start
September 2024

Fees
Fee Information

Modules
Module Information

81 percent of Computer Science and Informatics research outputs are intternationally recognised Top 50 University 2022

Funding and Scholarships

Discover the funding options available to you.

Discover NU World / A virtual journey through everything Northumbria has to offer.

Explore our immersive 360 tours, informative subject videos, inspirational student profiles, ground-breaking research, and a range of life at university blogs videos and articles.

Discover More / Advanced Computer Science MSc

Watch Programme Leader Dr. Ammar Belatreche gives an introduction to the Advanced Computer Science MSc, and explore the facilities.

Entry Requirements 2024/25

Standard Entry

Applicants should normally have:

A minimum of a 2:2 honours degree in a computing-related discipline which included programming in an object-oriented language, system analysis and design, databases, computer operating systems and networks. Other subject qualifications, equivalent professional qualifications and/or relevant work experience will be considered on an individual basis.

International qualifications:

If you have studied a non UK qualification, you can see how your qualifications compare to the standard entry criteria, by selecting the country that you received the qualification in, from our country pages. Visit www.northumbria.ac.uk/yourcountry

English language requirements:

International applicants are required to have a minimum overall IELTS (Academic) score of 6.5 with 5.5 in each component (or 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 you will need in our English Language section. Visit www.northumbria.ac.uk/englishqualifications

Fees and Funding 2024/25 Entry

Full UK Fee: £10,460

Full EU Fee: £19,750

Full International Fee: £19,750



Scholarships and Discounts

Discover More about Fees, Scholarships and other Funding options for UK, EU and International applicants.

ADDITIONAL COSTS

There are no Additional Costs

If you’d like to receive the latest updates from Northumbria about our courses, events, finance & funding then enter your details below.

* At Northumbria we are strongly committed to protecting the privacy of personal data. To view the University’s Privacy Notice please click here

How to Apply

Please use the Apply Now button at the top of this page to submit your application.

Certain applications may need to be submitted via an external application system, such as UCAS, Lawcabs or DfE Apply.

The Apply Now button will redirect you to the relevant website if this is the case.

You can find further application advice, such as what to include in your application and what happens after you apply, on our Admissions Hub Admissions | Northumbria University



Modules

Module information is indicative and is reviewed annually therefore may be subject to change. Applicants will be informed if there are any changes.

KF7014 -

Advanced Programming (Core,20 Credits)

In this module you will learn about current software best practices and software development architectures. This module will cover a range of topics that will enable you to research and develop best practices for designing and developing applications that are based around microsystem architectures.
The module will cover a range of topics, such as:
1. Application architecture design
2. Understanding ‘Tech Stacks’
3. Monolithic vs Microservice architecture
4. Communication protocols (e.g., API, message broker, services mesh)
5. Development pipelines

More information

KF7028 -

Research Methods and Project Management (Core,20 Credits)

In this module you will learn about research and the processes involved in carrying out research in the area of computer and information sciences. The module will encompass the full research cycle from development of the initial concept through to final evaluation and reflection on your research. You will learn how to search, find and evaluate the literature and how to use this to construct a critical literature review. You will also be able to gain an understanding of different research methods and techniques and how to apply them in practice. You will be given the opportunity to gain expertise in data and information analysis, from data collection through to the analysis, presentation and interpretation of results. You will be able to critically evaluate and reflect on the research process. You will also learn about ethics and professional conduct whilst undertaking research and consider and manage risk (including health and safety) and legal, societal and sustainability issues with respect to a research project.

Alongside this you will be provided with the skills and techniques to effectively manage a project from start to finish, including the planning and monitoring aspects.

More information

KF7029 -

MSc Computer Science & Digital Technologies Project (60 Credits)

The aim of this module is to enable you to undertake a substantial academic research project at Masters level, record your progress though this, and present the results from your research in both written and oral forms. Your research project will be a major piece of independent and original research centred at the forefront of your programme discipline within the wider sphere of computer and information sciences.

You will experience the full life cycle of a research project from initial conception and development of a research proposal, through a critical review of the literature, planning, design, implementation and analysis of your main research project, to final evaluation, reflection and dissemination. You will be expected to conduct your research in an ethical and professional manner, and manage risk and consideration of the legal, societal and sustainability issues applicable, to this academic research project. You will also be expected to apply your expertise, project management and practical skills within your particular domain of computer and information sciences and demonstrate critical and innovative thinking and problem solving within a research environment.

More information

KF7031 -

Wireless Networks and Security (Optional,20 Credits)

This module is designed to be suitable for a variety of networking professional roles including those wishing to gain a deeper understanding of 802.11 protocols, security and mobile networks and their security protocols, their weaknesses and how to protect against known attacks.. Additionally, it is suitable for wireless network administrators and support or design staff requiring a greater understanding of the new technologies and applications of modern converged networks and delegates seeking Certified Wireless Security Professional certification. Below are the learning outcomes of the module:
Critical appraisal of the global nature of WLAN standards and design
To gain critical understanding of the core concepts in wireless and mobile communication technologies, modelling of wireless channel, security threats and vulnerabilities associated with wireless networks.
Critically analyse security protocols associated with wireless local area networks (WLANs) as well as apply specialist knowledge to design and evaluate a secure wireless network.
Critically evaluate and apply suitable security measures to protect wireless networks against known vulnerabilities.
Demonstrate ability to work in culturally diverse groups and teams and make appropriate and personal contributions to team effectiveness

More information

KF7032 -

Big Data and Cloud Computing (Core,20 Credits)

In this module you will develop knowledge and skills that will enable you to tackle a realistic big data problem, using some of the principal machine learning techniques and statistical approaches used in big data analysis. Furthermore, you will learn how to implement your solution using an industry leading Cloud computing provider together with appropriate distributed processing environments.

You will learn how to host multi-terabyte sized big datasets using a cloud service provider. This will includes provisioning a commercial cloud provider, and then mastering appropriate distributed operating systems, such as Hadoop. You will then learn approaches to processing and analysing big data, based on advanced statistical processing, supervised and unsupervised machine learning algorithms and other state of the art big data analytic methods. Such techniques include clustering algorithms, pattern based information extraction, linear and non-linear regression, and feature based models. Inevitably, much work on big data analysis is statistical, so you will therefore develop some relevant statistical understanding. As data visualization is frequently critical in helping to develop hypotheses about the data, you will also cover and apply problem relevant 2D and 3D visualization methods where appropriate to the particular datasets.

More information

KL7011 -

Advanced Databases (Core,20 Credits)

In this module, you will learn about the entire data life cycle (from creation to disposal) and will gain a deep understanding of classical database development processes and approaches to modelling, design and management of databases. You will be able to learn and employ data warehousing techniques to integrate and consolidate data from different sources, which can then be used for business reporting, exploratory data analysis and advanced data analytics. In addition, you will realise the responsibilities of database designers with respect to professional, legal, security and ethical issues as well as undertaking risk management and evaluation of commercial risk in relation to data management. Moreover, you get an appreciation of non-traditional data types, systems and applications (e.g., NoSQL Databases), data standards and data quality. The module will covers topics such as:

• An overview of the entire data life cycle (e.g., creation, modelling, representation, usage, maintenance, disposal, etc)
• Classical data engineering processes and approaches (modelling, design, implementation and management and access of databases)
• Data warehousing
• Non-traditional data management technologies (e.g., NoSQL databases)
• Data analytics
• Data standards and data quality

More information

KV7001 -

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 institution 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 area in the Department of Architecture and Built Environment. 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.
• Giving discipline-related academic presentations, experiencing peer observation, and receiving formative feedback.
• Speed reading techniques.
• Discussing ethical issues in research, and analysing results.
• Describing bias and limitations of research.
• Developing self-reflection skills.

More information

KV7002 -

Human-Computer Interaction for Social Change (Optional,20 Credits)

Human-Computer Interaction (HCI) is a field of study focusing on the interaction between humans and computers. The way that social life is organised influences the computer interfaces that we design – HCI traditionally concerns itself with satisfying user needs and requirements based on our social interactions. But, technologies also change (sometimes fundamentally) the things that we do and how we do them in the course of our everyday lives. Sometimes this is deliberate and driven by opposing value systems, as in the case of the use of interactive technologies in supporting revolution, activism, citizen science for advocacy e.g. for social change. Sometimes new technologies enable and bring about new forms of living, working, or participation in civic society that disrupt existing ones, as with Uber, AMT, and social networking platforms like Twitter.

In this module you will specifically explore how to design, develop and evaluate technologies for social change, from a human-centred perspective.

Indicative topics that we will cover include (but are not limited to):

Principles of Human-Centred Design for interactive technologies
Understanding people, context, and social life: Theories, Social media, Instrumented environments
Mock-ups, Prototyping and User Interface tools and toolkits
Participatory design
Designing to provoke: Adversarial design, Critical design
Designing for the future: Speculative design, Design fiction
Interaction qualities and experiences: Slow technology, Designing for Non-use, Counterfunctional design
Evaluation techniques: Action research, Field studies, Usability labs (eye tracking)
Specific Application Areas: HCI and environmental sustainability, ICT for Development (ICT4D), The future of: Health, Work, Money, Digital Civics

More information

KV7006 -

Machine Learning (Optional,20 Credits)

In this module you will develop knowledge and skills that will enable you to tackle a realistic machine learning problem, using some of the principal advanced machine learning techniques. You will also learn about recent applications of machine learning. Furthermore, you will learn how to implement machine learning based solutions and evaluate their performance using real world examples. The main topics covered in this module include:

• Mathematical foundations of machine learning
• Supervised, Unsupervised and reinforcement learning
• Feature extraction, feature selection and dimensionality reduction
• Classification and clustering techniques
• Optimisation techniques
• Ensemble techniques
• Autoencoders
• Deep generative models
• Deep Learning
• Data visualisation

More information

Modules

Module information is indicative and is reviewed annually therefore may be subject to change. Applicants will be informed if there are any changes.

KF7014 -

Advanced Programming (Core,20 Credits)

In this module you will learn about current software best practices and software development architectures. This module will cover a range of topics that will enable you to research and develop best practices for designing and developing applications that are based around microsystem architectures.
The module will cover a range of topics, such as:
1. Application architecture design
2. Understanding ‘Tech Stacks’
3. Monolithic vs Microservice architecture
4. Communication protocols (e.g., API, message broker, services mesh)
5. Development pipelines

More information

KF7028 -

Research Methods and Project Management (Core,20 Credits)

In this module you will learn about research and the processes involved in carrying out research in the area of computer and information sciences. The module will encompass the full research cycle from development of the initial concept through to final evaluation and reflection on your research. You will learn how to search, find and evaluate the literature and how to use this to construct a critical literature review. You will also be able to gain an understanding of different research methods and techniques and how to apply them in practice. You will be given the opportunity to gain expertise in data and information analysis, from data collection through to the analysis, presentation and interpretation of results. You will be able to critically evaluate and reflect on the research process. You will also learn about ethics and professional conduct whilst undertaking research and consider and manage risk (including health and safety) and legal, societal and sustainability issues with respect to a research project.

Alongside this you will be provided with the skills and techniques to effectively manage a project from start to finish, including the planning and monitoring aspects.

More information

KF7029 -

MSc Computer Science & Digital Technologies Project (60 Credits)

The aim of this module is to enable you to undertake a substantial academic research project at Masters level, record your progress though this, and present the results from your research in both written and oral forms. Your research project will be a major piece of independent and original research centred at the forefront of your programme discipline within the wider sphere of computer and information sciences.

You will experience the full life cycle of a research project from initial conception and development of a research proposal, through a critical review of the literature, planning, design, implementation and analysis of your main research project, to final evaluation, reflection and dissemination. You will be expected to conduct your research in an ethical and professional manner, and manage risk and consideration of the legal, societal and sustainability issues applicable, to this academic research project. You will also be expected to apply your expertise, project management and practical skills within your particular domain of computer and information sciences and demonstrate critical and innovative thinking and problem solving within a research environment.

More information

KF7031 -

Wireless Networks and Security (Optional,20 Credits)

This module is designed to be suitable for a variety of networking professional roles including those wishing to gain a deeper understanding of 802.11 protocols, security and mobile networks and their security protocols, their weaknesses and how to protect against known attacks.. Additionally, it is suitable for wireless network administrators and support or design staff requiring a greater understanding of the new technologies and applications of modern converged networks and delegates seeking Certified Wireless Security Professional certification. Below are the learning outcomes of the module:
Critical appraisal of the global nature of WLAN standards and design
To gain critical understanding of the core concepts in wireless and mobile communication technologies, modelling of wireless channel, security threats and vulnerabilities associated with wireless networks.
Critically analyse security protocols associated with wireless local area networks (WLANs) as well as apply specialist knowledge to design and evaluate a secure wireless network.
Critically evaluate and apply suitable security measures to protect wireless networks against known vulnerabilities.
Demonstrate ability to work in culturally diverse groups and teams and make appropriate and personal contributions to team effectiveness

More information

KF7032 -

Big Data and Cloud Computing (Core,20 Credits)

In this module you will develop knowledge and skills that will enable you to tackle a realistic big data problem, using some of the principal machine learning techniques and statistical approaches used in big data analysis. Furthermore, you will learn how to implement your solution using an industry leading Cloud computing provider together with appropriate distributed processing environments.

You will learn how to host multi-terabyte sized big datasets using a cloud service provider. This will includes provisioning a commercial cloud provider, and then mastering appropriate distributed operating systems, such as Hadoop. You will then learn approaches to processing and analysing big data, based on advanced statistical processing, supervised and unsupervised machine learning algorithms and other state of the art big data analytic methods. Such techniques include clustering algorithms, pattern based information extraction, linear and non-linear regression, and feature based models. Inevitably, much work on big data analysis is statistical, so you will therefore develop some relevant statistical understanding. As data visualization is frequently critical in helping to develop hypotheses about the data, you will also cover and apply problem relevant 2D and 3D visualization methods where appropriate to the particular datasets.

More information

KL7011 -

Advanced Databases (Core,20 Credits)

In this module, you will learn about the entire data life cycle (from creation to disposal) and will gain a deep understanding of classical database development processes and approaches to modelling, design and management of databases. You will be able to learn and employ data warehousing techniques to integrate and consolidate data from different sources, which can then be used for business reporting, exploratory data analysis and advanced data analytics. In addition, you will realise the responsibilities of database designers with respect to professional, legal, security and ethical issues as well as undertaking risk management and evaluation of commercial risk in relation to data management. Moreover, you get an appreciation of non-traditional data types, systems and applications (e.g., NoSQL Databases), data standards and data quality. The module will covers topics such as:

• An overview of the entire data life cycle (e.g., creation, modelling, representation, usage, maintenance, disposal, etc)
• Classical data engineering processes and approaches (modelling, design, implementation and management and access of databases)
• Data warehousing
• Non-traditional data management technologies (e.g., NoSQL databases)
• Data analytics
• Data standards and data quality

More information

KV7001 -

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 institution 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 area in the Department of Architecture and Built Environment. 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.
• Giving discipline-related academic presentations, experiencing peer observation, and receiving formative feedback.
• Speed reading techniques.
• Discussing ethical issues in research, and analysing results.
• Describing bias and limitations of research.
• Developing self-reflection skills.

More information

KV7002 -

Human-Computer Interaction for Social Change (Optional,20 Credits)

Human-Computer Interaction (HCI) is a field of study focusing on the interaction between humans and computers. The way that social life is organised influences the computer interfaces that we design – HCI traditionally concerns itself with satisfying user needs and requirements based on our social interactions. But, technologies also change (sometimes fundamentally) the things that we do and how we do them in the course of our everyday lives. Sometimes this is deliberate and driven by opposing value systems, as in the case of the use of interactive technologies in supporting revolution, activism, citizen science for advocacy e.g. for social change. Sometimes new technologies enable and bring about new forms of living, working, or participation in civic society that disrupt existing ones, as with Uber, AMT, and social networking platforms like Twitter.

In this module you will specifically explore how to design, develop and evaluate technologies for social change, from a human-centred perspective.

Indicative topics that we will cover include (but are not limited to):

Principles of Human-Centred Design for interactive technologies
Understanding people, context, and social life: Theories, Social media, Instrumented environments
Mock-ups, Prototyping and User Interface tools and toolkits
Participatory design
Designing to provoke: Adversarial design, Critical design
Designing for the future: Speculative design, Design fiction
Interaction qualities and experiences: Slow technology, Designing for Non-use, Counterfunctional design
Evaluation techniques: Action research, Field studies, Usability labs (eye tracking)
Specific Application Areas: HCI and environmental sustainability, ICT for Development (ICT4D), The future of: Health, Work, Money, Digital Civics

More information

KV7006 -

Machine Learning (Optional,20 Credits)

In this module you will develop knowledge and skills that will enable you to tackle a realistic machine learning problem, using some of the principal advanced machine learning techniques. You will also learn about recent applications of machine learning. Furthermore, you will learn how to implement machine learning based solutions and evaluate their performance using real world examples. The main topics covered in this module include:

• Mathematical foundations of machine learning
• Supervised, Unsupervised and reinforcement learning
• Feature extraction, feature selection and dimensionality reduction
• Classification and clustering techniques
• Optimisation techniques
• Ensemble techniques
• Autoencoders
• Deep generative models
• Deep Learning
• Data visualisation

More information

Any Questions?

Our Applicant Services team will be happy to help.  They can be contacted on 0191 406 0901 or by using our Contact Form.



Accessibility and Student Inclusion

Northumbria University is committed to developing an inclusive, diverse and accessible campus and wider University community and are determined to ensure that opportunities we provide are open to all.

We are proud to work in partnership with AccessAble to provide Detailed Access Guides to our buildings and facilities across our City, Coach Lane and London Campuses. A Detailed Access Guide lets you know what access will be like when you visit somewhere. It looks at the route you will use getting in and what is available inside. All guides have Accessibility Symbols that give you a quick overview of what is available, and photographs to show you what to expect. The guides are produced by trained surveyors who visit our campuses annually to ensure you have trusted and accurate information.

You can use Northumbria’s AccessAble Guides anytime to check the accessibility of a building or facility and to plan your routes and journeys. Search by location, building or accessibility feature to find the information you need. 

We are dedicated to helping students who may require additional support during their student journey and offer 1-1 advice and guidance appropriate to individual requirements. If you feel you may need additional support you can find out more about what we offer here where you can also contact us with any questions you may have:

Accessibility support

Student Inclusion support




All information is accurate at the time of sharing. 

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.  

Contact time is subject to increase or decrease in line with possible restrictions imposed by the government or the University in the interest of maintaining the health and safety and wellbeing of students, staff, and visitors if this is deemed necessary in future.

 

Useful Links

Find out about our distinctive approach at 
www.northumbria.ac.uk/exp

Admissions Terms and Conditions
northumbria.ac.uk/terms

Fees and Funding
northumbria.ac.uk/fees

Admissions Policy
northumbria.ac.uk/adpolicy

Admissions Complaints Policy
northumbria.ac.uk/complaints



If you’d like to receive the latest updates from Northumbria about our courses, events, finance & funding then enter your details below.

* At Northumbria we are strongly committed to protecting the privacy of personal data. To view the University’s Privacy Notice please click here

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Get an insight into life at Northumbria at the click of a button! Come and explore our videos and 360 panoramas to immerse yourself in our campuses and get a feel for what it is like studying here using our interactive virtual tour.

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