About this course
About
BSc Hons Computing Systems develops core skills in problem solving and computational thinking and exposes you to topics spanning programming, databases, networking, web development, data analytics and product and process management. Advanced topics include systems security, cloud computing, applied artificial intelligence, computer vision and edge & embedded computing. The course also develops innovative and creative thinking alongside a range of professional, ethical and sustainable skills that prepare you for a career in computing, equipped with the technical and personal skills sought by industry and ready to apply best practice in software engineering to develop wide ranging systems for any organisation.
Uniquely, BSc Computing Systems is designed using the Variable Rate Progression (VRP) model. VRP empowers you to design your own personal pathway through the modules of the course, something that is not possible in traditional courses. The precise pathway, course duration and specific sequencing of modules are determined by you. Using VRP, the degree may be completed part-time in 3*, 4, 5 or 6 years. Many potential pathways exist. A pathway 'Simulator' for experimenting and planning your route through the course is available on our VRP website at: http://www.vrpassistant.com.
*Note that should you choose to enter the course in February, rather than September, the minimum duration of the course will be 4 years.
Ulster University is an approved Training Provider for the Department for the Economy's Higher Level Degree Apprenticeship** scheme. Students enrolled in the part-time BSc Hons Computing Systems program study alongside Degree Apprentices. Additionally, many scheduled lectures are shared with full-time Computing students. This blend of part-time students, degree apprentices, and full-time learners creates a vibrant and engaging learning environment, fostering opportunities for sharing experiences, collaboration, and building a lasting network of professional contacts.
** Applicants seeking an apprenticeship should visit Ulster's Degree Apprentice Hub wesite for additional guidane - https://www.ulster.ac.uk/apprenticeships
The School of Computing at Ulster University holds Athena Swan Bronze Award since 2016 and is committed to promote and advance gender equality in Higher Education. We particularly welcome female applicants, as they are under-represented within the School.
Modules
Here is a guide to the subjects studied on this course.
Courses are continually reviewed to take advantage of new teaching approaches and developments in research, industry and the professions. Please be aware that modules may change for your year of entry. The exact modules available and their order may vary depending on course updates, staff availability, timetabling and student demand. Please contact the course team for the most up to date module list.
In this section
- Level 4 – studied in Year 1 or 2
- Level 5 – studied in Year 2, 3 or 4
- Level 6 – studied in Year 3, 4, 5 or 6
Level 4 – studied in Year 1 or 2
Semester 1
Problem Solving for Computing
Computer programming is a fundamental skill expected of computing graduates. This module will introduce students to the foundational concepts of programming via Python that will be used as building blocks in future modules. Students will also develop and enhance their problem solving skills as an integral part of the module.
Introduction to Databases
Database management is a fundamental skill expected of Computing graduates. This module will introduce students to the fundamental concepts of database design, implementation, querying and management of relational database systems.
Semester 2
Innovation and Society
This module is designed to make future computing professionals have the practical skills to cocreate innovative technological solutions to a problem using design thinking tools and processes and be aware of and take into consideration the nature of the legal, ethical, social and professional issues raised during any technological innovation.
Mathematics for Computer Scientists
This module provides an introduction to core areas of mathematics that are commonly used by computer scientists. The relationship between set theory and propositional logic is explained, with applications to digital circuits. Mathematics for decision making is introduced, including their practical application. Probability, descriptive statistics and matrices are introduced, and their application to simple linear regression is used to motivate their use within data science.
Semester 3
Client Side Development
This module will assume no prior experience in creating web pages and will introduce the design principles, structural elements and technical concepts that underpin web authoring.
Application of the technical concepts will be facilitated through the use of web authoring tools in practical sessions to enhance the technical skills for the creation and styling of interactive Websites.
Introduction to Physical Computing
The aim of this module is to provide an understanding of the underlying systems that support the applications software. The theoretical concepts covered are illustrated by considering their practical application in modern real-world solutions.
Level 5 – studied in Year 2, 3 or 4
Semester 1
Programming in Practice
The module builds upon the expertise acquired in Level 4 programming modules by expanding upon the students' understanding of data types and algorithms within the scope of object-oriented programming. The module focuses on providing students with practical skills for industry-focused software development.
Systems Security
This module introduces fundamental concepts related to computer system security. It presents a thorough discussion of the fundamental principles and technologies underpinning the field, covering concepts, terminology, cryptography, vulnerabilities, protocols and good security-oriented design.
The module provides an understanding of computing systems security concerns and how they can be addressed and mitigated so that security considerations are taken into account, and embedded in organisations and IT projects planning and management. This includes the communications within networked applications, security issues and cryptographic fundamentals
Semester 2
Software Product and Process Management
The Software Product and Process Management module provides the opportunity for students to gain a sound theoretical understanding of contemporary product and process management techniques. There is also the opportunity to apply learning from within the module and from modules undertaken thus far while working cohesively and professionally as part of a software team towards the successful management and planning of software product that meets business needs.
Data Analytics
In the present-day era of big data, this module will provide students with the theory and hands-on practical programming experience required for the undertaking of real-world data analytics tasks.
Semester 3
Computer Networking
Computer networks are at the core of relatively large and modern computing systems. This module aims to equip learners with the appropriate skills to appreciate, understand and employ the key technologies used by interconnected devices in any networks. The module introduces the students to the basics of the networking field including components, topologies, architectures, functions, services, protocols, and standardisation.
Server Side Development
This module will expand on students' knowledge necessary for developing software systems to be deployed over the World Wide Web, with a specific focus on server-side technologies and techniques. Students will also be introduced to important design considerations for web applications currently in use in industry.
Level 6 – studied in Year 3, 4, 5 or 6
Semester 1
Full-Stack Strategies and Development
This module will introduce the key concepts of full-stack development and the tools used to implement a full-stack strategy. Students will be able to use what they learn from this module to develop robust software including APIs, database architectures and front-end applications according to industry standards.
Cloud Native Development
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 cloud architectures, hosted technologies, scalable solutions and infrastructure will be explored. Additionally, advanced programming/development concepts facilitating high performance solution development will be examined.
Semester 2
Artificial Intelligence
This module is optional
The AI module is built on the foundations in mathematics, computing and programming. It covers logic based symbolic AI, knowledge representation and reasoning, introduction to machine learning paradigms and advanced learning methods of reinforcement and deep learning, and real-world applications in different human-AI interactions. The module will answer the following three questions: (1) how to formulate AI problems conceptually; (2) how to turn the conceptual formulations into algorithms; (3) how to develop AI-focused applications. The module will also consider societal and theoretical concerns raised while designing and deploying AI solutions regarding the ability of people to understand, interpret, control, and interact with AI-based systems.
Computer Vision
This module is optional
Computer Vision is an increasingly pervasive element of technology-based solutions in a range of applications, both standalone and distributed over the Internet, requiring an understanding of image and video processing fundamentals and how they are integrated with Machine Learning. This module seeks to develop the student's knowledge of Computer Vision by introducing techniques and tools that enable machines with a capacity to sense the world using visual data. The module also provides opportunities for the student to learn how to develop applications to solve Computer Vision tasks and to implement solutions using Computer Vision and Machine Learning software tools and libraries.
Semester 3
Edge and Embedded Intelligence
This module is optional
This module explores the intersection between machine learning and embedded systems. The aim of Edge and Embedded Intelligence is to make Artificial Intelligence available on low-powered and computationally constrained devices such as microcontrollers. This module provides a foundation for students to understand this emerging field.
Enterprise Networks
This module is optional
The module provides the student with a deep understanding of the underlying communication protocols of personal, local area networks, wide area networks and inter-networks. The emphasis is on network planning, design and management. Issues such as acceptable network performance, detection of faults, maintaining security and effective management are studied as these are key to the successful operation of businesses. The module will address state of the art protocols and network case studies and can provide (i) an up to date viewpoint of Enterprise Networks for business and (ii) an opportunity for fostering research ideas in this discipline.
Semester 1/2 ** or Semester 2/3
Computing Project)
** The Computing Systems project is typically undertaken during Semesters 2 and 3 of the final year of study. Students may elect to undertake the Computing Project during Semesters 1 and 2, provided they have no more than one new Semester 1 taught module remaining.
The Computing Project provides an opportunity to draw together learning from across the course, and to allow students to evidence their mastery of the academic content and of its application through professional practice. Through the opportunity to devise, manage and evaluate all aspects of work in addressing a significant challenge, students can gain independence and a deeper appreciation of their practice within the broader subject area and of its relationship to wider society.
Attendance
During Semesters 1 and 2 BSc Hons Computing Systems is delivered one day per week, typcially on a Monday. During Semester 3, students attend for 6 full days of intensive block training per module selected, normally scheduled across June and July. The timetabled contact hours for the course accounts for around 25% of the expected self-directed study time for each module.
The duration of the degree is dependent on the number of modules you study and successfully completed each year. There are six modules at each of three levels in the course. Each year, you can choose to undertake a minimum of three modules and a maximum of six modules. This choice aims to enhance flexibility and empowers you to complete the course in as little as three years or to choose a slower track lasting four, five or even six years. You will have an annual opportunity to review and adjust your rate of progress. Module optionality normally exists at Level 6.
Start dates
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September 2024
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February 2025
Teaching, Learning and Assessment
The course is delivered using several teaching and learning methods including Lectures, Tutorials and Practical Laboratory Session.
Lectures are used to present and illustrate basic theory and fundamental principle, which are normally supplemented by tutorials which elaborate on lecture content and provide opportunities for the student to use their problem-solving skill and to examine problem solutions in greater detail.
Practical Laboratory Classes enable the practical application of theoretical concepts, facilitating a deeper understanding of key topics. In programming laboratories, there is an emphasis on small group tutoring and support.
Modules are assessed through a wide variety of methods including practical skills assessment, written reports, oral presentations, recorded video submissions, class tests, collaborative coursework assignments,and a final year cap-stone project.
Attendance and Independent Study
The content for each course is summarised on the relevant course page, along with an overview of the modules that make up the course.
Each course is approved by the University and meets the expectations of:
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Attendance and Independent Study
As part of your course induction, you will be provided with details of the organisation and management of the course, including attendance and assessment requirements - usually in the form of a timetable. For full-time courses, the precise timetable for each semester is not confirmed until close to the start date and may be subject to some change in the early weeks as all courses settle into their planned patterns. For part-time courses which require attendance on particular days and times, an expectation of the days and periods of attendance will be included in the letter of offer. A course handbook is also made available.
Courses comprise modules for which the notional effort involved is indicated by its credit rating. Each credit point represents 10 hours of student effort. Undergraduate courses typically contain 10, 20, or 40 credit modules (more usually 20) and postgraduate courses typically 15 or 30 credit modules.
The normal study load expectation for an undergraduate full-time course of study in the standard academic year is 120 credit points. This amounts to around 36-42 hours of expected teaching and learning per week, inclusive of attendance requirements for lectures, seminars, tutorials, practical work, fieldwork or other scheduled classes, private study, and assessment. Teaching and learning activities will be in-person and/or online depending on the nature of the course. Part-time study load is the same as full-time pro-rata, with each credit point representing 10 hours of student effort.
Postgraduate Master’s courses typically comprise 180 credits, taken in three semesters when studied full-time. A Postgraduate Certificate (PGCert) comprises 60 credits and can usually be completed on a part-time basis in one year. A 120-credit Postgraduate Diploma (PGDip) can usually be completed on a part-time basis in two years.
Class contact times vary by course and type of module. Typically, for a module predominantly delivered through lectures you can expect at least 3 contact hours per week (lectures/seminars/tutorials). Laboratory classes often require a greater intensity of attendance in blocks. Some modules may combine lecture and laboratory. The precise model will depend on the course you apply for and may be subject to change from year to year for quality or enhancement reasons. Prospective students will be consulted about any significant changes.
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Assessment
Assessment methods vary and are defined explicitly in each module. Assessment can be a combination of examination and coursework but may also be only one of these methods. Assessment is designed to assess your achievement of the module’s stated learning outcomes. You can expect to receive timely feedback on all coursework assessments. This feedback may be issued individually and/or issued to the group and you will be encouraged to act on this feedback for your own development.
Coursework can take many forms, for example: essay, report, seminar paper, test, presentation, dissertation, design, artefacts, portfolio, journal, group work. The precise form and combination of assessment will depend on the course you apply for and the module. Details will be made available in advance through induction, the course handbook, the module specification, the assessment timetable and the assessment brief. The details are subject to change from year to year for quality or enhancement reasons. You will be consulted about any significant changes.
Normally, a module will have 4 learning outcomes, and no more than 2 items of assessment. An item of assessment can comprise more than one task. The notional workload and the equivalence across types of assessment is standardised. The module pass mark for undergraduate courses is 40%. The module pass mark for postgraduate courses is 50%.
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Calculation of the Final Award
The class of Honours awarded in Bachelor’s degrees is usually determined by calculation of an aggregate mark based on performance across the modules at Levels 5 and 6, (which correspond to the second and third year of full-time attendance).
Level 6 modules contribute 70% of the aggregate mark and Level 5 contributes 30% to the calculation of the class of the award. Classification of integrated Master’s degrees with Honours include a Level 7 component. The calculation in this case is: 50% Level 7, 30% Level 6, 20% Level 5. At least half the Level 5 modules must be studied at the University for Level 5 to be included in the calculation of the class.
All other qualifications have an overall grade determined by results in modules from the final level of study.
In Masters degrees of more than 200 credit points the final 120 points usually determine the overall grading.
Figures from the academic year 2022-2023.
Academic profile
The teaching and support of the programme is provided by the academic staff in the School of Computing and School of Engineering.
The academic members of staff are active in a range of research areas that inform the modules in the course. The School also employs Teaching Fellows who fulfil the duties of Module Coordinators but provide specialist support in laboratory classes and programming clinics across the course including final year project support. Graduate Demonstrators and Research staff support the academic staff who teach on the course.
Academic staff in the School are qualified to teach in higher education with most of them holding at least a Postgraduate Certificate in Higher Education Practice. Most academic staff in the School (83%) are accredited fellows of the Higher Education Academy (HEA) – the university sector professional body for teaching and learning.
The University employs over 1,000 suitably qualified and experienced academic staff - 59% have PhDs in their subject field and many have professional body recognition.
Courses are taught by staff who are Professors (25%), Readers, Senior Lecturers (18%) or Lecturers (57%).
We require most academic staff to be qualified to teach in higher education: 82% hold either Postgraduate Certificates in Higher Education Practice or higher. Most academic staff (81%) are accredited fellows of the Higher Education Academy (HEA) - the university sector professional body for teaching and learning. Many academic and technical staff hold other professional body designations related to their subject or scholarly practice.
The University employs over 1,000 suitably qualified and experienced academic staff - 60% have PhDs in their subject field and many have professional body recognition.
Courses are taught by staff who are Professors (19%), Readers, Senior Lecturers (22%) or Lecturers (57%).
We require most academic staff to be qualified to teach in higher education: 82% hold either Postgraduate Certificates in Higher Education Practice or higher. Most academic and learning support staff (85%) are recognised as fellows of the Higher Education Academy (HEA) by Advance HE - the university sector professional body for teaching and learning. Many academic and technical staff hold other professional body designations related to their subject or scholarly practice.
The profiles of many academic staff can be found on the University’s departmental websites and give a detailed insight into the range of staffing and expertise. The precise staffing for a course will depend on the department(s) involved and the availability and management of staff. This is subject to change annually and is confirmed in the timetable issued at the start of the course.
Occasionally, teaching may be supplemented by suitably qualified part-time staff (usually qualified researchers) and specialist guest lecturers. In these cases, all staff are inducted, mostly through our staff development programme ‘First Steps to Teaching’. In some cases, usually for provision in one of our out-centres, Recognised University Teachers are involved, supported by the University in suitable professional development for teaching.
Figures from the academic year 2022-2023.
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.
A level
CCC.
Applied General Qualifications
QCF Pearson BTEC Level 3 Extended Diploma / OCR Cambridge Technical Level 3 Extended Diploma (2012 Suite)
award profile DMM.
RQF Pearson BTEC Level 3 National Extended Diploma / OCR Cambridge Technical Level 3 Extended Diploma (2019 Suite)
award profile DMM.
RQF Pearson BTEC Level 3 National Extended Diploma / OCR Cambridge Technical Level 3 Extended Diploma (2016 Suite)
MMM overall award grades.
A Levels with:
BTEC Level 3 QCF Subsidiary Diploma or BTEC Level 3 RQF National Extended Certificate;
BTEC Level 3 QCF 90-credit Diploma or BTEC Level 3 RQF National Foundation Diploma;
BTEC Level 3 QCF Diploma or BTEC Level 3 RQF National Diploma.
OCR/Cambridge Technical Combinations
A levels with OCR Nationals and OCR Cambridge Technicals.
Irish Leaving Certificate
96 UCAS Tariff Points to include a minimum of 4 subjects at Higher Level and 1 subject at Ordinary Level. The overall profile must also include English and Maths at Grade H6 or above (HL) or Grade O4 or above (OL).
Irish Leaving Certificate UCAS Equivalency
Tariff point chart
Scottish Highers
Grades CCCCC. All subject areas considered.
Scottish Advanced Highers
Grades DDD. All subject areas considered.
International Baccalaureate
Overall profile of 24 points to include 12 at Higher Level to inlcude grade 4 in Mathematics and Grade 4 in English Language.
Access to Higher Education (HE)
Overall profile of 55% (120 credit Access) (NI Access Course) to include a pass in NICATS Maths (level 2) or GCSE Maths at Grade C or 4.
Overall profile of 45 Merits (60 credit Access Course) (GB Access Course) to include GCSE Maths at Grade C or 4.
GCSE
GCSE (or equivalent) profile to include minimum of Grade C or 4 or above in Mathematics and Grade C or 4 in English Language.
Please note that for purposes of entry to this course the Level 2 Certificate in Essential Skills - Application of Number is NOT regarded as an acceptable alternative to GCSE Maths.
English Language Requirements
English language requirements for international applicants
The minimum requirement for this course is Academic IELTS 6.0 with no band score less than 5.5. Trinity ISE: Pass at level III also meets this requirement for Tier 4 visa purposes.
Ulster recognises a number of other English language tests and comparable IELTS equivalent scores.
Additional Entry Requirements
HNC
Pass HNC with overall Merit in a relevant subject area for year 1 entry only to include distinctions in 45 Level 4 credits to include GCSE Maths at Grade C or 4.
HND Year 1
Pass HND in any subject area. GCSE Maths Grade C/4 or an alternative Mathematics qualification acceptable to the University is also required.
HND Year 2
Pass HND rwith overall Merit in a relevant subject area. To include GCSE Maths at Grade C or 4. HND applications may be considered for year 2 entry where the curriculum sufficiently matches that of Ulster University full time year 1 course.
Ulster Foundation Degree
Pass in Foundation Degree with an overall mark of 40% and minimum 40% in all taught level 5 modules. To inlcude GCSE Maths at Grade C or 4. Applicants will normally be considered for entry to an associated Honours degree (normally Year 2 entry if FD in a relevant subject area).
Exemptions and transferability
Transfers are processed in accordance with the Faculty Admissions Policy for dealing with transfer requests from existing students.