Program Overview

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Computer Science with Industrial Placement - MSc

Overview

Creating the next generation of high-quality professionals for the Computer Science industry.

Summary

“Computer scientists understand the underlying principles of programming and algorithms and use them to design software, systems and networks to meet the needs of clients and the public. It is a fast-moving, highly specialised field and there is a constant, high demand for talented computer science graduates.”

The MSc Computer Science is a specialist programme that has the core aim of preparing students for both an industrial career, equipped with a comprehensive understanding of the advanced concepts, paradigms, algorithms, theories and techniques underpinning advanced computing systems, in addition to providing a relevant platform to embark on further research studies. The course covers leading-edge subjects in areas of Advanced Computer Science, Artificial Intelligence and Internet of Things.

About this course

About

The MSc award consists of two compulsory taught modules (totaling 40 credits), four optional taught modules (totaling 80 credits) from a wide range of topics, in addition to a substantial piece of independent Masters Project (60 credits). As part of the programme, students will be required to use various programming languages, including Python and R.

The two compulsory modules are:

• Scalable Advanced Software Solutions This module aims to explore a range of modern development and deployment concepts in the context of scalable and high-performance computing services. Within this module concepts such as containerisation, Continuous Integration, Continuous Delivery, cloud architectures, scalable solutions and infrastructure will be explored. Additionally, advanced programming/development concepts facilitating high performance solution development will be examined.
• Data Science and Machine Learning This module provides an overview of Data Science process/pipeline. It provides systematic understanding of mathematical and statistical knowledge for exploratory data analysis (EDA) and to understand the foundations of supervised and unsupervised machine learning algorithms, and with the practical programming skills to apply them to real world datasets. The module discusses the constraints that needs to be considered when designing, implementing, evaluating and visualising solutions to real-world complex problems.

Example optional modules are:

• Cyber Security Cyber security, which has an impact on national security, infrastructure, and the global economy, is one of today's most pressing issues. Due to the enormous digital threat, cyber security knowledge is among the most in-demand globally. This course examines recent advancements in cyber security theory and practice. To enable critical cyber security decision-making, the students will develop the fundamental and advanced aspects of cyber security in terms of theory, practice, policy, and security standards. They will also learn about the threats to current and emerging systems and networks and how to effectively counter them in accordance with information security management standards. The students will learn about the social, legal, and ethical issues surrounding cyber security.
• Deep Learning and Its Application The module will introduce the fundamentals of deep learning, construction of neural networks and theory of developing successful deep learning algorithms. Students 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 develop solutions for applications of computer vision and natural language processing.
• Big Data and Infrastructure Within this module a variety of database and data storage paradigms will be explored, ranging from more traditional relational systems to NoSql and object stores, time series databases, semantic store and graph stores. Consideration will be given to big data and the problem with storing and querying high volumes of highly variable data which is stored and processed at a high speed. The cloud computing paradigm will also be introduced and how to avail of its power and resources. The core concepts of distributed computing will be examined in the context of a data lake. Students will be taught, practically and theoretically, about the components of Data lakes, workflows, functional programming concepts, use of MapReduce, Spark, Pig, and Hive.
• IoT Networks and Protocols The Internet of Things (IoT) describes the interconnectivity of uniquely identifiable devices embedded in the environment through internet protocols and infrastructure. The module will evaluate and critically appraise IoT networking concepts, models, standards, protocols and practical skills. It will address Sustainability Development Goals, inform on the evolving IoT use cases, and appraise related issues such as the impact of IoT on a citizen’s privacy.
• Robotics & AI This module provides an overview of smart robotics and AI. It is designed to provide students with a strong foundation through the core topics and the key technologies of robotics and AI while providing hands-on experience on programming smart robots in the labs. The module will explore practically coding AI techniques for Robotics and the focus is given to design and implement smart robots exhibiting AI behaviours.
• Pervasive Computing The focus of this module is to provide an opportunity for students to gain an in-depth understanding of pervasive computing and to apply this understanding to a range of application domains through developing specific solutions for selected application case studies. The module surveys emerging hardware and software components associated with Pervasive Computing Systems, examining the technical and societal issues concerned with a pervasive infrastructure, wireless networks, protocols and emergent algorithms. In doing so a number of examples of innovative systems and applications are reviewed. The module includes a strong practical element where students will be asked to develop services providing support for wearable and smart home context-aware solutions.
• Knowledge Engineering This module will cover modern topics in a classical field of artificial intelligence, including knowledge representation and reasoning (deductive and inductive), and their effective utilisation in e.g. decision making, automated reasoning and formal verification, and semantic web. Students will gain deep understanding of key concepts and principles, and gain practical skills in critically evaluating and effectively building knowledge-based applications.
• Intelligence Engineering and Infrastructure The aim of this module is to educate students on best practices for engineering, deploying, testing and orchestration intelligence across modern computing. This will include aspects of Machine learning, federated operation of activities, data engineering, production of tailored computational artefacts (such as models which are tailored for a range of device type), production pipelines, automated testing and automated deployment.
• Emerging and Advanced Topics in AI This module will cover cutting-edge topics in the field of artificial intelligence, including recent advances in AI theory, algorithms and applications, as well as issues such as privacy, fairness and ethics in artificial intelligence. In doing so a number of examples of advanced AI systems and applications are reviewed. Students will gain deep understanding of key concepts, principles, and challenges, and gain practical skills in critically evaluating and effectively building AI-based applications. The module will also help students develop their skills in independent learning, research skills, writing, as well as practical skills in using software to reproduce results from the literature.
• Embedded Systems and Sensors An embedded system is an electronic or computer system which performs dedicated control and data access functions in electronics-based systems and applications. Embedded systems play crucial role in modern communications, automotive systems, consumer electronics and medical devices and will provide the foundation for the next generation of inclusive and sustainable, smart and connected Internet-of-Things (IoT) solutions. This module covers the most important aspects of the embedded systems and will provide a successful student with theoretical and practical knowledge on the feasibility, reliability, and security of electronic systems, especially those important for existing and future IoT applications.

Attendance

Typically 15 timetabled hours per week Monday – Friday including lectures, tutorials and practicals in the computer labs for the taught components of the course. Research Project takes place in the third semester separately. The industrial placement is normally 12 months in duration in the second year of MSc programme.

Start dates

• September 2026
• January 2027

Teaching, Learning and Assessment

Teaching is delivered through lectures, directed tutorials, seminars, and practical sessions, some of which are by industry professionals / researchers.

The course is assessed by 100% coursework.

Academic profile

Academic staff in the School of Computing are qualified to teach in higher education with most of them holding at least a Postgraduate Certificate in Higher Education Practice. The majority of academic staff in the School are accredited fellows of the Higher Education Academy (HEA) or above.

Standard entry conditions

We recognise a range of qualifications for admission to our courses. In addition to the specific entry conditions for this course you must also meet the University’s General Entrance Requirements.

Entry Requirements

• Applicants must have gained
  • (i) an upper second class honours degree or better, in the subject areas of Computer Science, Software Engineering, Electronic Engineering, Electrical Engineering, Mathematics, Physics or closely related discipline, from a university of the United Kingdom or the Republic of Ireland, or from a recognised national awarding body, or from an institution of another country which has been recognised as being of an equivalent standard;
  • (ii) an equivalent standard (normally 50%) in a Graduate Diploma, Graduate Certificate, Postgraduate Certificate or Postgraduate Diploma or an approved alternative qualification excluding Conversion courses; and the qualification must be in the subject areas of Computer Science, Software Engineering, Electronic Engineering, Electrical Engineering, Mathematics, Physics or closely related discipline.

English Language Requirements

Applicants must provide evidence of competence in written and spoken English (GCSE grade C or equivalent). For applicants whose first language is not English the minimum English language requirement is an Academic IELTS 6.0 with no band score less than 5.5, Trinity ISE: Pass at level III or equivalent English language tests comparable to IELTS equivalent score.

Careers & opportunities

Career options

Recent predictions from the US Department of Labor Bureau of Labor Statistics have indicated that the Computer and IT field will grow by 13% between the period . This is faster than the average rate of growth of all occupations. The MSc Computer Science specialist programme aims to provide postgraduate education and training in the area of Computer Science and its application to the needs of the industrial community. The course is designed to meet the demand for a new kind of Computing specialist who is able to both manage data, understand business process and implement solutions subsequently interconnecting them as part of a larger system. Graduates from the MSc Computer Science will be well placed to progress into a wide variety of careers, across a range of industrial settings and application domains. There are also opportunities for graduates from the MSc Computer Science to embark on further research by enrolling for PhD study affiliated with the research centres within the School of Computing. Computing related PhD studies in the areas of Pervasive Computing and Artificial Intelligence can be perused within the School of Computing.

Work placement / study abroad

Students who have successfully completed the taught modules and Masters Project of their MSc programme, and have secured an internship of twelve months duration with a suitable company, are eligible to proceed to the Industrial Placement pathway. This pathway provides masters students with an opportunity to gain structured and professional work experience at an advanced level, in a work-based learning environment, as part of their planned programme of study at the University. This will allow students to further develop, refine and reflect on their key personal and professional skills. The placement opportunity should significantly support the development of the student's employability skills, build confidence through further application of theory within the workplace and prepare them for a future career in computing. It also serves as an integrating mechanism for course content as well as developing analytical, evaluative and project management skills in an industrial context. The nature of the work will vary depending on the company providing the placement. The student will complete a reflective professional development report and learning journal as part of the assessment of this pathway.

Professional Recognition

Accreditations reflect the excellence of our teaching, research, and knowledge exchange and ensure our programmes realise the highest expectations. By studying at Ulster University you’ll gain insight and be at the forefront of current industry practices, while our many accredited degree programmes open doors to the world’s top professional organisations, making you more attractive to future employers and giving you a competitive edge in the job market.

BCS, the Chartered Institute for IT

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.

BCS, the Chartered Institute for IT

Accredited by BCS, the Chartered Institute for IT for the purposes of partially meeting the academic requirement for registration as a Chartered IT Professional.

Fees and funding

10% Alumni Discount

Are you a graduate of Ulster University? Did you know you could be eligible for a 10% fees discount.

Tuition Fee Loans Available

Students domiciled in Northern Ireland, Republic of Ireland and UK students can apply to Student Finance NI for a Tuition Fee loan of up to £6,500 (subject to eligibility).

2026/27 Fees

Postgraduate fees are subject to annual review, 2026/27 fees will be announced in due course.

See our tuition fees page for the current fees for 2025/26 entry.

View Available Scholarships

See if you can access financial or other forms of support, including mentorship to excel in your studies.

Search our Scholarships (Opens in a new window)

Additional mandatory costs

It is important to remember that costs associated with accommodation, travel (including car parking charges) and normal living will need to be covered in addition to tuition fees.

Where a course has additional mandatory expenses (in addition to tuition fees) we make every effort to highlight them above. We aim to provide students with the learning materials needed to support their studies. Our libraries are a valuable resource with an extensive collection of books and journals, as well as first-class facilities and IT equipment. Computer suites and free Wi-Fi are also available on each of the campuses.

There are additional fees for graduation ceremonies, examination resits and library fines.

Students choosing a period of paid work placement or study abroad as a part of their course should be aware that there may be additional travel and living costs, as well as tuition fees.