|Level of study:||Postgraduate degree|
|Tuition Fees||Fees and Finances|
A 2:2 honours degree, or equivalent, in the subject areas of computing, engineering, mathematics or related discipline
|English language requirements:|
IELTS 6.0 with no component less than 5.5, or equivalent
Other English language tests are accepted, click here to find out more.
|Mode of study:||Full-time|
|Start dates:||January, September, May (24)|
This programme is subject to approval
About this course
The UK economy is facing a well-documented digital skills gap, costing an estimated £63 billion a year in potential GDP, prompting the Government to launch various initiatives to address this issue, including the designated Institute of Coding and the announcement of a Digital Skills Strategy to make the UK a global tech superpower. Recent estimates predict that by 2025 there will be 3 million new tech vacancies in the UK and 149 million world-wide.
The MSc in Computer Science and Technology will provide you with the knowledge and practical experience of the advanced concepts, algorithms, theories and techniques underlying advanced computing systems for a successful career in this booming industry.
The course covers leading-edge subjects of programming such as:
- Big Data
- Deep learning
- Data mining
- Machine learning
- Statistical modelling — the most up-to-date topics in the areas of Computer Science, Artificial Intelligence and Data Science.
- Scalable Software Solutions leveraging Cloud Infrastructure
This programme is also available as MSc in Computer Science and Technology with Advanced Practice , which includes either an internship or project.
- You will be taught using a wide variety of teaching methods across the modules including lectures, seminars and tutorials. Typically, you will have 12-17.5 hours of contact time per week.
- In addition to your time in class, you will also be expected to engage in approximately 35 hours of self-study time per week.
- You will have access to Blackboard, our online learning environment, where you can access module resources and reading lists that will assist your preparation for classes and self-study.
- You’ll be taught by experienced lecturers and academics who use their industry and research experience to demonstrate how to apply best practice in software engineering to the development of a wide range of information systems in organisations.
Each module is assessed by coursework only.
Careers and postgraduate opportunities
Student and employer needs are reflected in the development of this programme and evidenced in the career destinations and further development of our graduates.
Graduates will be prepared for a range of careers across a variety of sectors, with some of the roles including:
- Software Engineers
- Software Developers
- IT Engineers
- IT Project ad Programme Managers
- Machine Learning Engineers
- Artificial Intelligence Practitioners
- Data Scientists
- Deep Learning Engineers
All modules are core and 20 credits unless specified.
In this module, you’ll be introduced to contemporary server environments and related concepts, commands, their management and operation.
You will gain practical and theoretical experience with the scalable, cloud-based, architectures offered by solutions providers such as OpenStack, Amazon Web Services and Azure.
Additionally, you will examine advanced programming/development concepts facilitating high performance solution development.
Knowledge Engineering deals with the process of developing, maintaining, extending, and using knowledge-based systems that use (symbolic) artificial intelligence methods.
This module will introduce you to the fundamentals of knowledge engineering, including terminology and concepts, core models and algorithms, technologies, and application scenarios.
You will explore the knowledge engineering toolkit that can be applied to build knowledge-based applications.
You will gain deep understanding of key concepts and principles and gain practical skills in critically evaluating and effectively building knowledge-based applications.
Big Data is the term for a collection of datasets so large and complex that they become difficult to process using traditional database tools.
In this module, you will explore different ways of storing data, including:
- Traditional relational systems
- NoSQL and object stores
- Time series databases
- Semantic stores and graph stores
You will also learn about cloud computing and how to use it to access more resources. Additionally, you’ll explore the core concepts of distributed computing in the context of a data lake, including:
- Components of data lakes
- Functional programming concepts
- Use of MapReduce, Spark, Pig, and Hive
In this module, you’ll learn about digital transformation and how it can impact an organisation’s business model, products, and structure using digital technologies.
Digital technologies such as the Internet, social media, data analytics, and cloud computing have eliminated traditional boundaries of time and geography and created virtual communities with new demands for products and services. It has allowed businesses to improve productivity, reduce costs, and innovate.
By the end of this module, you’ll understand the impact of digital transformation in various organisational contexts, and you’ll be able to apply tools and frameworks to plan and implement a digital transformation strategy.
In this module, you’ll learn about data science and machine learning techniques that are used in many industries, including healthcare, finance, and sport. You will learn how these techniques are integrated into software applications and other solutions.
By the end of the module, you’ll have the knowledge and skills to understand the role of data science and machine learning in various industries and apply them to real-world problems.
The module will introduce a fundamental knowledge of deep learning and help you develop your ability to implement effective solutions to practical applications.
You will learn state of the art convolutional neural networks, recurrent neural networks, loss functions and optimisation process along with development tools, and apply them to the development of solutions for deep learning application domains (i.e., Sequential data analysis, Computer Vision, Natural Language Processing, etc.)
This module is designed to provide you with the opportunity to implement the knowledge gained throughout this course and conduct in-depth literature research to solve a problem drawn from the research area.
The project will involve design, implementation, experimentation, and critical analysis of results.
The project will test your creativity, critical thinking abilities, project management, problem-solving skills and in-depth knowledge.
You will also learn how to analyse and critically evaluate concepts and demonstrate the ability to successfully conduct an independent programme of research and analysis with the aim of developing new knowledge and recommendations.
*Please note the course content is subject to approval
The course information displayed on this page is correct for the academic year 2023/24. We aim to run the course as advertised however, changes may be necessary due to updates to the curriculum (due to academic or industry developments), student demand or UK compliance reasons.
- A 2:2 (second class) honours degree or International equivalent in the subject areas of computing, engineering, mathematics or related discipline
- In exceptional circumstances, if you do not meet the entry requirements above but have substantial and significant experiential learning, you may be able to apply as a non-standard applicant.
For country-specific entry requirements, please visit the entry requirements page.
If you are unsure whether your qualifications meet the entry requirements, please contact us and one of our team will contact you to discuss your options.
English language requirements
Applicants must satisfy our general entry requirements as well as meeting specific requirements.
- You will need to provide evidence of competence in written and spoken English (GCSE grade 4 – previously grade C – or equivalent).
The general entry requirements are any of the following:
- IELTS 6.0 with no band score less than 5.5, or equivalent
If you do not have the required IELTS, you may be eligible to study on our Pre-Sessional programmes.
Tuition fees for 2023/24
- UK/Home students: £8,250
- London: £14,700
- Birmingham: £13,050
Please note: UK/Home students who are financing their studies through the postgraduate loan, you will be required to make a deposit payment of £250 at enrolment, this amount will be deducted from the total tuition fee. This does not apply to progressing students who are currently studying at the undergraduate level with us.
Please note that the fees outlined are for your tuition only and do not include the cost of any course books that you may choose to purchase, stationery, accommodation etc. As an Ulster University London and Birmingham branch campus student you will also have access to our on-campus libraries and a range of e-learning resources.
The modules you will study may require you to purchase additional course textbooks and you should be prepared to buy some additional texts, we recommend allowing an additional £300 for the duration of your course.
Information for international students
Ulster University is committed to providing the best possible experience to all our students. To ensure you secure your place with us, we require our international students to pay a deposit towards their fees. More information can be found here.
What does my tuition pay for?
- Your teaching in class – this includes seminars, lectures and tutorials
- Access to facilities including computers, Wi-Fi, printers, lockers, multi-faith rooms, quiet study space and social areas. To learn more about available facilities please visit our London or Birmingham branch campus pages
- Our library service – both on-campus and an extensive online catalogue of resources
- Careers and Employability Service which provides help with CVs, applications and interview preparation through workshops, drop-ins and 1-2-1 appointments
- The ACE Team (Academic Community of Excellence) who are here to support you with your studies and assignments
- Students Activities Association (SAA) – who organise events on campus, discounted sightseeing trips and help students create and run societies
Scholarships and discounts
For self-funding students, we offer a range of scholarships and early payment fee discounts, you can find out more here.
How to find out more
To find out more about this course, we recommend that you complete our enquiry form and one of our team will contact you to discuss your options.
How to apply
UK and International students can apply directly to study the MSc Computer Science and Technology via our online application form below.
APPLY FOR JANUARY 2024
|Birmingham||Apply for January 2024|
|London||Apply for January 2024|
Information for disabled applicants
At Ulster, we welcome applications from disabled students and are committed to ensuring an equal and accessible application journey. Your application will be considered on an equal basis to all other applications. Please contact us if you require any assistance. This website is continually optimised to adhere to accessibility best practice guidelines; tools to assist users with specific accessibility requirements have also been provided. More information is available in our accessibility statement.
If you’re not sure or have any questions about studying with us, please contact us and one of our team will be able to help.