STUDY
Course options: | Professional Placement |
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Institution code: | S82 |
UCAS code: | I103 |
Start date: | September 2025 |
Duration: | Three/four years full-time, four and a half to nine years part-time |
Location: | Ipswich |
Typical Offer: | 112 UCAS tariff points (or above) BBC (A-Level) DMM (BTEC), Merit (T Level) |
Course options: | Professional Placement |
---|---|
Institution code: | S82 |
UCAS code: | I103 |
Start date: | September 2025 |
Duration: | Three/four years full-time, four and a half to nine years part-time |
---|---|
Location: | Ipswich |
Typical Offer: | 112 UCAS tariff points (or above) BBC (A-Level) DMM (BTEC), Merit (T Level) |
Overview
Our flexible BSc (Hons) Computing degree equips you with the practical industry knowledge you need to meet the demand for skilled computing professionals. The course offers a flexible computing curriculum with diverse learning pathways, with the freedom to forge your own course by selecting specialist modules.
You’ll benefit from the resources of leading tech giants Amazon Web Services, Juniper, Oracle, and our new Google Student Club, and experience world-class specialist labs at our state-of-the-art DigiTech Centre, which is home to over 150 high-tech ICT companies and BT’s innovation labs.
You’ll engage in real-world projects alongside industry leaders, leveraging cutting-edge technologies and embrace an annual slate of industry events and hackathons to apply your acquired skills. You’ll also have the chance to launch your own venture through the University of Suffolk’s Innovation Labs (ILABS), guided by business leaders and academics.
Course Pathways
BSc (Hons) Computing (Cyber Security)
BSc (Hons) Computing (Web and Mobile Development)
BSc (Hons) Computing (Artificial Intelligence)
Create your own pathway
Combine a wide range of modules in cyber security, software engineering, web design, mobile development, networking, data science, AI, cloud computing, and more, to create a custom curriculum. This degree has been designed to allow you to flexibly follow your interests, whilst ensuring that you reach the advanced knowledge necessary for industry roles through theory and practice.
At the start of your course, you will be allocated a Personal Academic Coach who can explain the options and pathways available so you will always be supported in the decisions you make and can be sure they align with your career ambitions. Students that choose to create their own pathway will be awarded a BSc (Hons) Computing degree upon completion of the course.
Computing at the University of Suffolk
Student Projects
Course Modules
Our undergraduate programmes are delivered as 'block and blend', more information can be found on Why Suffolk? You can also watch our Block and Blend video.
Downloadable information regarding all University of Suffolk courses, including Key Facts, Course Aims, Course Structure and Assessment, is available in the Definitive Course Record.
This module covers the principles of computer systems, hardware components, the essence of operating systems, and relevant computing-related mathematics. This module will provide the foundational underpinning to enable students to progress deeper into different computing specialisms, and a grasp of the history of computing, recent developments and its possible future.
This module introduces the concepts of communications and networking. It explores the Open Systems Interconnectivity (OSI) 7-layer reference model and TCP/IP Routing Suite (the 5-layer Internet reference model). TCP/IP is the model which is most commonly deployed in the majority of modern-day networks.
The module introduces the concepts of web design, with a focus on designing responsive websites that are targeted at mobile platforms. Students are introduced to HTML, CSS and JavaScript to provide them with an understanding of what goes into the front-end of modern websites. Using a series of case studies, students will analyse the design and layout of a range of existing sites using a number of common analysis techniques.
This module introduces students to the concepts and practice of computer programming. It is aimed at providing students with an understanding of the fundamentals of computer programming by having them work through a range of tasks focused upon layout, structure and functionality.
This module provides an understanding of why cyber security matters to businesses, to society and to individuals, coupled with knowledge of basic concepts, attack techniques, attacker types, and the core elements of cyber assurance.
This module provides an introduction to the artificial intelligence and data science fields, covering the history of the discipline, and exploring a variety of “classical AI” topics.
This module focuses on all phases of the modern software engineering lifecycle and advanced software engineering topics, including critical software, secure software, formal methods and project management from the practitioner’s perspective. This will be put into practice through the requirements gathering, design, implementation and testing of an extensive project that meets the needs of a particular enterprise.
This module provides essential knowledge and appreciation of the role of relational database systems, including basic principles and practice of design, implementation and development for both system designers and software engineers. It will include practical exercises in Structured Query Language.
Research skills are an essential set of capabilities in the toolkit of a professional software engineer. In this module, students will develop knowledge and understanding of the purpose, processes, methods (surveys, experiments, interviews, case studies, etc.), analysis (qualitative and quantitative), and outputs of research and will be able to apply them. This module also delves into the professional, legal and ethical standards and guidelines that inform and guide best practice in business and computing.
This module focuses on data structures (e.g. linked lists, trees, heaps, hash tables, etc), algorithms (sorting, searching, dynamic programming, greedy, graph, geometric, cryptographic, string matching and compression algorithms, etc), and advanced programming techniques and other language paradigms.
The module builds upon the content delivered to the students in Introduction to Web Design, providing students with an advanced understanding of front-end web development and design technologies. Essential for any career in the web industry, students will utilise advanced frameworks, pre-processors and design patterns to create interactive, accessible and mobile-friendly web interfaces. Through interactive hands-on sessions, students will develop their own online portfolio of work and become familiar with the prototyping and agile development methodologies common to the web industry.
The module will provide students with the knowledge and skills needed to develop scalable server-side applications utilising a range of influential web technologies. Throughout the module, there is an emphasis on preparing students for the web industry by ensuring best practices are followed and industry-standard software and tools are used. Additional topics such as security, ethical hacking, APIs and encryption will also be taught to ensure students have the skills required to design and develop large-scale web infrastructures.
Software, networks and databases do not exist in isolation, but form part of systems. Few systems are purely technical, but are socio-technical and info-socio-technical in nature, where human beings may be central or peripheral to the system, yet be the weakest link in their security. This module introduces, in the context of cyber security, system thinking and human behaviour, and how social engineering and open-source intelligence may be used in both attack and defence of systems and individuals.
Data science includes many techniques for classification, analysis and prediction. This module focuses on those techniques relating to data mining and statistically driven approaches. These techniques also have the advantage of being “explainable AI”, more so than deep learning approaches, and some are long established techniques of “business intelligence”.
This module covers basic and advanced security concepts related to wired and wireless networks, and builds upon the network knowledge previously covered in Level 4 study. Students will learn about the main challenges faced by a variety of wired and wireless environments. Further, the module presents common defence techniques and tools used to counter different security threats, and also explores some of the latest network security challenges posed by recent technology developments.
Industry, commerce and research are being transformed by the potential to capture, store, manipulate, analyse and visualise data and information on a massive scale. The advent of Big Data with its variety, velocity and volume disrupted the way we store and manage data. During this module you will learn NoSQL approaches to data modelling, database design and manipulation.
The module provides the opportunity for students to apply and develop some of the knowledge and skills acquired in their degree by engaging in a significant project in a specialist area of computing, typically software or networks. It will enable and require students to utilise practical, intellectual and decision-making skills in novel situations and develop their autonomy and self-direction.
Cyber security is now an executive-level concern in most organisations. Cyber security specialists will be required to deliver strategic value to their organisations by ensuring security is intrinsic to system architectures by design and by default, by applying appropriate standards in risk analysis, systems modelling and policy design, and scanning the horizon of emergent threat landscapes to discern new issues.
This covers the full range of skills and knowledge required for “Big Data” including parallel and NoSQL databases, statistical modelling and programming, machine learning, data analytics and visualisation. These skills are essential for making sense of security-related Big Data.
A sufficiency of inexpensive computing power, sufficiently large datasets and a number of key theoretical advances created deep learning techniques which have facilitated a wave of accuracy increases across many computational tasks (computer vision, natural language processing, speech recognition, autonomous driving, etc.), making many applications practical. Deep learning is central to modern artificial intelligence. This module explains the underlying mathematics and techniques and how to use them to achieve similar feats of computational accuracy.
This module provides an opportunity to explore in greater depth several areas of artificial intelligence and data science. This will include an understanding of the domain theory, typical problems faced in the domain and how these might be solved.
The module is intended to provide students with an understanding of development for mobile devices with a focus on the constraints of mobile hardware, including interface and networking. Students will learn to integrate input from hardware sensors and work with networked data and services.
This module provides a systematic understanding of distributed operating systems, software services and applications in terms of their architectures, functionality and behaviour. It includes case studies on the “Internet of Things” and cloud computing as well as topics on parallel programming.
There has been a triple convergence of computing, communications and the physical world, leading to the creation of complex cyber-physical systems, a reliance on strong cryptography, and the need to instil security into software and cyber-physical systems in the face of an ever-evolving threat landscape.
Cyber attacks are increasing in frequency and diversity with hostile actors probing for vulnerabilities, cooperating to develop exploits, and deploying these on an industrial scale. Many organisations are essentially under continuous attack from multiple actors. Eternal vigilance through monitoring and logging is essential for reactive and proactive responses. Inevitably some attacks will be successful and effective actions are required to handle these incidents, limit breaches, and collect evidence for investigation.
On one hand, this provides insights into the mindset of cyber attackers, a secure understanding of the ethics and legal issues in this area, and knowledge and skills in attack technologies and techniques. On the other hand, this module provides a detailed knowledge and understanding of the techniques and tools available to a security professional, and the practical skills in selecting, evaluating, designing, implementing and deploying defences to protect vulnerable software, networks and systems.
WHY SUFFOLK
2nd in the UK for Career Prospects
WUSCA 20243rd in the UK for spend on academic services
Complete University Guide 20254th in the UK for Teaching Satisfaction
Guardian University Guide 2024Entry Requirements
Career Opportunities
Upon graduation from this degree, students can progress into a range of roles, including:
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Cyber Security Expert
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Web Developer
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Data Scientist
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Artificial Intelligence Expert
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Mobile App Developer
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QA Engineer
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Network Engineer
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Software Developer
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Data Analyst
All graduates will also have the opportunity to start their own business within the University of Suffolk Innovation Centre (IWIC). Here, students will have access to hot desk space, networking and collaborative opportunities.
Facilities and Resources
The majority of teaching on this degree will take place on our main Ipswich Waterfront campus and on the top floor of the Atrium building, which houses four high-end computer laboratories complete with industry-standard software and tools.
Specialist modules in data science, artificial intelligence and cyber security may also take place in our state-of-the-art DigiTech Centre at Adastral Park, which was unveiled by Her Royal Highness the Princess Royal in November 2019 and launched in the summer of 2021. The Cyber Security and Digital Forensics Laboratory at Digitech is an advanced facility equipped with high-specification machines. It provides a controlled environment where students can simulate cyberattacks, conduct forensic investigations, and delve into activities such as malware analysis, penetration testing, and cryptographic analysis without affecting other campus networks. In addition, the lab features top-tier Digital Forensics Equipment, which includes high-spec computers and acquisition kits complete with hardware write blockers for forensic image capture from various digital devices.
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