This highly desirable Bachelor of Computer Science degree is designed to equip you with the practical, future-focused skills needed for the fast-evolving world of technology.
You’ll study core foundations including algorithms, programming, software engineering, AI, cybersecurity, big data and smart systems, applying them in projects that reflect how technology is developed in industry.
Upon successful completion of your bachelor’s degree, if you meet entry requirements you will then have the option to take one of the many master’s pathways with the #1 university for innovation in the US (11 years running) Arizona State University. Through this partnership, you’ll gain access to a wide range of specialisations from the highly ranked W. P. Carey School of Business – one of the top business schools in the United States.
With flexible pathways in Software Development, Cybersecurity, or Big Data, you can shape your studies around your professional ambitions and emerging industry trends.
This degree programme will help you enter the technology sector with confidence, ready to make an impact. You’ll have the practical experience, technical expertise, and professional skills that employers value, including teamwork, communication, project management, and ethical decision-making.
You’ll also build a solid foundation in algorithms, computational theory, and software systems, develop coding skills with object-oriented programming and core data structures, and explore how hardware and software connect through sensors, actuators, and feedback.
Undertaking a design challenge, you’ll demonstrate your leadership and impact in engineering. Working on a real-life global challenge, underpinned by the UN Sustainability Goals, you’ll cover environmental, ethical, commercial, social, governance and cultural aspects of engineering.
Reflecting on your strengths and contributions, you’ll develop your teamwork, research, communication and problem-solving skills. These key skills are important for developing your professionalism as an engineer.
You’ll dive into the world of computer science, breaking problems down, designing smart algorithms, and representing data in clever ways. You’ll explore how computers actually ‘think’, experiment with real-world challenges like scheduling tasks or keeping data secure and use tools like Python and GitHub to bring your ideas to life.
Along the way, you’ll also look at the big picture, how computing shapes society, the environment, and everyday life. By the end, you won’t just understand how digital systems work, you’ll be ready to start building them yourself. It’s hands-on, creative, and gives you the foundations to tackle everything from coding to ethical tech design.
Here, you’ll level up your programming skills by learning to think and code like a professional software developer. You’ll get hands-on with object-oriented programming (OOP), building software using classes, objects, and smart design patterns that make your code clean, efficient, and reusable. Through coding labs, workshops, and projects, you’ll take on real-world challenges, sharpen your debugging skills, and create your own portfolio of programming work. You’ll also explore how coding choices impact people and the planet, from the energy your algorithms use to how inclusive your designs are. By the end, you’ll have the skills and confidence to create software that’s not only powerful but also responsible and future-focused.
Get ready to take control (literally) as you explore the world of smart systems. Learn how sensors, actuators, and control systems work together to bring machines and devices to life. Analyse how machines sense, react, and make decisions. Design and simulate control systems, the kind that keep robots balanced, cars on course, and industrial systems running smoothly.
Using industry software such as MATLAB/Simulink and microcontroller platform (e.g. Arduino), you’ll build simulations, analyse system responses, and design control strategies. Through structured coding exercises and practical workshops, you’ll get comfortable working with feedback systems, transfer functions, and system stability.
By the end, you’ll be able to model dynamic systems, design and test controllers, and understand the role of sensors and actuators in smart, automated solutions. It’s a practical, project-based experience built around real tools and real challenges.
All modules are subject to change and availability. If a module changes after you have been made an offer, you’ll be notified before you start your course.
This is where your ideas meet action. You’ll immerse yourself in a team project with a real-world brief designing a product, system, or process that solves a genuine challenge. It’s not just about what you build it’s how you plan, research, test, and deliver something that works.
You’ll dig into how research fuels innovation. That means learning how to ask the right questions, gather evidence, and build a strong case for your solution. You’ll plan your project, manage change, deal with setbacks, and learn how to keep things moving when everything gets messy, just like in real engineering.
Every decision you make will need backing whether it’s technical, ethical, environmental or commercial. You’ll use design thinking, experiment with prototypes, and learn how to turn a great concept into something real. Alongside your team project, you’ll also develop your own proposal for a new idea that could be taken to market. It’s your chance to explore what matters to you and how you’d bring it to life.
You’ll come away with experience in research, leadership, business modelling, and creative problem-solving. By the end, you won’t just be talking about innovation, you’ll be driving it.
Ready to turn messy data into smart decisions? Here, you’ll take on the role of a data detective diving into real industrial data to uncover insights, spot patterns, and build intelligent tools that work.
You’ll get to grips with cleaning and shaping raw data so it tells a clear visual story. Then you’ll explore machine learning in action, training models, testing outcomes, and figuring out how systems can learn and improve. It’s all about building practical skills through hands-on tasks and real-world case studies.
You’ll explore the full spectrum of machine learning, from visualising complex data with tools like heatmaps and correlation plots, to training intelligent algorithms that learn from data, recognise patterns, and predict future behaviour with real-world impact. And it’s not just about the tech – you’ll also tackle the big questions around ethics, sustainability, bias, and data privacy. Just because a system can make an informed decision, doesn’t mean it should.
By the end, you’ll be able to take an industrial dataset, turn it into a story, and pitch your findings with clarity and confidence. You’ll also learn from the past using real examples of where AI failed – analysing what went wrong, and how it could’ve been avoided. It’s fast-paced, relevant, and right at the intersection of data, technology, and impact.
Introducing you to the principles, and tools of software engineering, focusing on the systematic development of reliable, maintainable, and efficient software systems. Building on your programming skills, you’ll learn how to apply engineering discipline to the design, construction, testing, and management of software projects.
Key topics include software development lifecycles, agile and iterative methodologies, requirements engineering, software architecture and design patterns, testing frameworks, version control, and documentation. Explore professional practice in collaborative development, emphasising teamwork, communication, and quality assurance.
You’ll also integrate ethical and sustainability considerations, such as designing software for accessibility, evaluating environmental impacts of development processes, and ensure inclusivity in team-based practices.
Providing you with the theoretical and practical knowledge required to design, implement, and manage databases. Learn relational database principles, SQL (Structured Query Language), and data modelling techniques including entity–relationship diagrams and schema normalisation.
In addition to relational models, you’ll be introduced to NoSQL paradigms to understand their role in modern applications such as cloud services, social media, and big data systems. Develop competence in evaluating the trade-offs between data consistency, availability, scalability, and performance.
We emphasise responsible practice in data management, covering legal, ethical, and sustainability issues such as GDPR compliance, data privacy, data lifecycle management, and energy efficiency in large-scale data infrastructures.
Introducing you to the design, structure, and operation of modern operating systems (OS), providing the knowhow to understand how computing resources are managed efficiently and securely.
Study core OS concepts including process management, scheduling, memory management, file systems, concurrency, and input/output handling. Practical experience is gained by experimenting with OS components, shell scripting, and simulation tools. You’ll also engage with security and sustainability aspects of operating systems, including access control, energy efficiency in resource scheduling, and the ethical implications of operating system design.
Discover how computers talk to each other and how to keep that communication safe. You’ll learn what really happens when data moves across the internet, from IP addresses and routing to how information is protected with encryption and authentication. You’ll get hands-on experience setting up small networks, analysing data packets, and testing for security vulnerabilities, all in a safe, supervised lab environment. Along the way, you’ll dive into real-world issues like privacy laws, ethical hacking, and the environmental impact of digital infrastructure. By the end, you’ll know how networks work, how to secure them, and why responsible cybersecurity matters in today’s connected world.
All modules are subject to change and availability. If a module changes after you have been made an offer, you’ll be notified before you start your course.
In your final year for your bachelor’s degree, you’ll focus on advanced topics and independent work. You’ll carry out a major individual project, applying advanced analysis and professional reporting, while also studying applied artificial intelligence. You’ll then choose a specialist pathway: Software Development | Cybersecurity | Big Data.
Integrate all your knowledge from your previous learning to complete a major individual project. You’ll be expected to use an analytical and methodological approach involving elements such as project planning, designing, implementation, testing, quality assurance and evaluation and you’ll present your findings in a formal setting. Your project will be a significant piece of work, possibly related to the UN Sustainable Development Goals, smart cities, big data or informed by an industry need.
This is where everything you’ve learned about AI gets put to work. You’ll take on a full data science project from sourcing a dataset to deploying a working model – all built to solve a real engineering challenge.
You’ll dive deep into advanced AI tools and techniques, including deep learning, reinforcement learning, and optimisation. You’ll design, train, and test models that aim to make engineering systems smarter, more efficient and productive.
It’s hands-on and practical. You’ll build AI models with real impact, tackling complex problems and evaluating how your solution performs, where it falls short, and how it could improve. You’ll also create a ‘model card’ to reflect on the limitations and ethical dimensions of your work, making sure your solutions are not just smart, but responsible too. Along the way, you’ll explore the wider impact of AI on society, the environment, and engineering itself. This is about applying AI with purpose, turning complex data into real-world results.
Take your software skills to the next level as you learn how to build, test, and maintain reliable, high-quality systems. You’ll uncover how professional developers ensure their code works perfectly, from designing smart automated tests to using frameworks and CI/CD tools that keep software running smoothly. Explore everything from unit and regression testing to test-driven and behaviour-driven development, gaining a full picture of what quality really means in software. Alongside the tech, you’ll think critically about ethics, inclusivity, and sustainability, because great software isn’t just functional, it’s responsible. By the end, you’ll know how to deliver code that’s efficient, ethical, and built to last.
Step into the world of large-scale, connected software and learn how the systems behind your favourite apps actually run. You’ll get hands-on with modern distributed architectures like microservices and event-driven systems, exploring how to design interfaces, manage APIs, and deploy containerised services to the cloud. Along the way, you’ll tackle real engineering challenges, keeping systems fast, reliable, secure, and scalable, while using industry practices like DevOps, CI/CD, and Site Reliability Engineering (SRE). You’ll also look at the wider impact of these systems, from data privacy and energy use to how global teams build and maintain inclusive, sustainable technology. By the end, you’ll know how to design and operate complex systems that perform brilliantly in the real world.
Connect the dots between complex systems and make software work together seamlessly. Discover how modern organisations link up different apps, services, and data sources, diving into integration patterns, middleware tools, and API management. Through hands-on projects, you’ll design and build integration solutions using technologies like REST, GraphQL, and message queues, learning how to balance performance, security, and reliability along the way. You’ll also think critically about the bigger picture, from protecting sensitive data to reducing the environmental impact of data-heavy systems. By the end, you’ll know how to design and manage powerful integrations that keep diverse systems running smoothly and responsibly.
Develop your software security skills and learn how vulnerabilities really work and how to stop them. Explore the most common weaknesses hackers exploit, like buffer overflows, injection attacks, and privilege escalation, while safely practising real techniques in a controlled lab environment. Alongside hands-on testing, you’ll learn how to write secure code, use analysis tools, and follow professional penetration testing and disclosure practices. You’ll also dive into the ethics and laws that shape cybersecurity, thinking about the real-world impacts of insecure systems on people, businesses, and the planet. By the end, you’ll know how to spot and fix vulnerabilities responsibly, turning potential exploits into stronger, safer software.
Design and build the apps that live in everyone’s pocket. You’ll understand how mobile applications work behind the scenes, from Android and iOS architecture to cross-platform frameworks and responsive UI/UX design. Through hands-on projects, you’ll create apps that connect to sensors, APIs, and cloud services while tackling real challenges like battery life, storage limits, and network issues. You’ll also explore what it means to design apps responsibly, thinking about accessibility, data privacy, and the environmental footprint of mobile tech. By the end, you’ll have the skills to build mobile apps that are not just fast and functional, but secure, sustainable, and ready for the real world.
Step into the front lines of network security and learn how to protect complex systems from modern threats. You’ll explore how to secure enterprise, cloud, and critical infrastructure networks, diving into cryptographic protocols, firewalls, VPNs, intrusion detection, and zero-trust architectures. Through practical exercises, you’ll evaluate risks, implement defences, and use professional tools to monitor and protect networks at scale. You’ll also consider the wider impact of security, from ethical monitoring and legal compliance to energy use and inclusive access. By the end, you’ll be ready to design and manage robust, responsible security strategies for high-stakes networks.
In the fast-paced world of cybersecurity operations learn how organisations defend themselves around the clock. You’ll explore how Security Operations Centres (SOCs) work, diving into log management, SIEM tools, threat intelligence, incident response, and even red/blue team exercises. Through hands-on practice, you’ll monitor, detect, and respond to cyber threats while learning the workflows and frameworks that keep networks safe. You’ll also tackle the bigger picture, balancing privacy, ethics, and sustainability, while understanding the human and organisational challenges of running a SOC. By the end, you’ll have the skills and insight to handle cyber incidents responsibly and effectively in a professional setting.
Equipping you with advanced knowledge and practical skills in digital forensics, focusing on the investigation, analysis, and presentation of evidence from digital systems. Explore forensic principles, methodologies, and tools used to acquire, preserve, and analyse evidence in compliance with legal and professional standards.
Core topics include forensic imaging, file system analysis, volatile memory capture, network forensics, mobile forensics, and anti-forensics techniques. You’ll also study chain of custody procedures, evidential integrity, and reporting standards for legal contexts.
Ethical, legal, and sustainability considerations are integrated throughout, including the rights of individuals in digital investigations, proportionality in evidence collection, privacy concerns, and the environmental costs of data storage and processing.
Step into the world where the digital meets the physical and learn how to keep cyber-physical systems safe. Explore the security challenges of industrial control systems, IoT networks, autonomous vehicles, and smart cities. Study how digital, physical, and human elements interact. Through case studies and hands-on analysis, you’ll examine real incidents like Stuxnet and attacks on critical infrastructure, learning how vulnerabilities were exploited and defended against. You’ll also consider the wider context, privacy, safety, environmental impact, and inclusivity, so your solutions aren’t just secure, but responsible and sustainable. By the end, you’ll be ready to design and evaluate advanced strategies that protect complex, real-world systems.
Dive into the cutting-edge world of federated cyber intelligence and learn how organisations collaborate to stay ahead of cyber threats. Explore frameworks like MITRE ATT&CK, data sharing protocols, and privacy-preserving analytics, seeing how intelligence can be gathered and analysed across sectors and borders. Through practical examples and case studies, you’ll tackle the challenges of trust, governance, and interoperability while learning how to use federated systems responsibly. You’ll also consider the ethical, legal, and environmental impacts of large-scale intelligence sharing. By the end, you’ll be able to design and evaluate federated cyber intelligence solutions that are effective, lawful, and sustainable.
Unlock the power of data and discover how to extract meaningful insights from complex, large datasets. Get hands-on with advanced statistical analysis, machine learning, and data visualisation, applying these techniques to real-world problems using professional tools and workflows. You’ll explore advanced methods like feature engineering, model selection, and exploratory analysis, while also considering the bigger picture, tackling issues like data bias, privacy, transparency, and the environmental impact of large-scale computing. By the end, you’ll be able to design and evaluate sophisticated data science solutions that are not just accurate, but responsible and impactful.
Providing you with advanced knowledge and practice in distributed database systems, focusing on the design, implementation, and evaluation of systems that manage data across multiple locations, nodes, or clouds. Study the principles of distribution, replication, partitioning, and consistency, and how these impact performance, reliability, and scalability. Core topics include distributed transaction processing, concurrency control, distributed query optimisation, fault tolerance, CAP/PACELC trade-offs, and database security in distributed environments. You’ll also explore modern platforms such as NewSQL, NoSQL clusters, and cloud-based distributed database services. Ethical, legal, and sustainability aspects are embedded throughout: data sovereignty and compliance with cross-border regulations, privacy in distributed data flows, inclusivity of global access, and the environmental footprint of distributed data infrastructures. By the end, you’ll be able to design, implement, and critically evaluate distributed database systems, balancing performance, resilience, compliance, and sustainability.
Advancing your skills in the design, implementation, and evaluation of big data systems that support large-scale data collection, storage, processing, and analysis. Explore the architectures and technologies underpinning big data platforms, including distributed file systems, stream-processing frameworks, and cluster resource management.
Core topics include data ingestion pipelines, batch and stream processing, distributed storage, cluster management, and the evaluation of performance, scalability, and fault tolerance. You’ll also study emerging trends such as serverless data systems and real-time analytics.
We embed ethical, legal, and sustainability considerations, including privacy in large-scale data processing, energy consumption of data centres, accessibility of global-scale data systems, and equitable access to data-driven technologies.
At the end, you’ll be able to design, implement, and critically evaluate big data systems, balancing technical performance with professional responsibility.
Develop your knowhow of computational methods for large-scale data processing, with a focus on high-performance techniques used in big data environments. Explore frameworks and hardware architectures that enable efficient computation over massive datasets, including GPU acceleration, distributed parallelism, and cloud-native computing models.
Core topics include parallel programming paradigms, GPU-based data processing, in-memory computing, distributed task scheduling, scalability of algorithms, and the optimisation of computational resources for performance and energy efficiency. You’ll engage with case studies from scientific computing, financial modelling, climate research, and AI applications to understand how big data computing supports decision-making in critical domains.
Ethical, inclusivity, and sustainability issues are embedded throughout, such as energy consumption of high-performance clusters, equitable access to computational resources, and responsible use of data-intensive computing in global contexts.
Explore advanced concepts and practices in regional data management, focusing on the technical, legal, and ethical issues of storing, processing, and governing data across different geographic, legal, and political jurisdictions.
Core topics include regulatory frameworks, data localisation policies, distributed and federated data architectures, metadata and governance standards, and the trade-offs between global interoperability and regional compliance. Analyse case studies where regional policies impact cloud platforms, multinational enterprises, and cross-border research collaborations.
Ethical, legal, and sustainability considerations are central to the module: ensuring data fairness and inclusivity, protecting individual rights, and addressing the environmental costs of regional data infrastructures such as duplicated storage and increased energy demand.
All modules are subject to change and availability. If a module changes after you have been made an offer, you’ll be notified before you start your course.
Our entry requirements are designed to open pathways to higher education for students from a wide range of academic backgrounds. Like Arizona State University, we measure our success not by whom we exclude, but by whom we include – and how well they thrive.
The criteria below are provided as a guide to help you determine whether ASU London is the right fit for you:
English language requirements: English level can only be demonstrated through an IELTS Academic for UKVI minimum score of 6.0 (with no less than 5.5 in all skills).
Visas: For more information on student visas and work rights, please visit our student visa page.
Scholarships: The Inaugural Global Scholarship is now open for international students. Learn more about funding opportunities here.
As soon as you start you’ll be on a fast-track to complete your bachelor’s degree and master’s degree in four years.
Typical assessment methods include:
This diverse approach allows you to demonstrate your skills and knowledge in multiple ways, while the most appropriate method is chosen at the module level to ensure a balanced assessment across the programme.
Group work is a key part of your learning, and a clear group working policy ensures it is fair, consistent, and reflective of professional practice.
Through this mix of assessments, you’ll build the ability to communicate, collaborate, and apply your knowledge in real-world scenarios, preparing you for future careers and industry challenges in IT and computer science.
As an undergraduate student, you will study modules totalling 120 credits each academic year. A typical 15 credit module requires a total of 150 hours study. This is made up of teaching contact hours, guided and independent study.
Our founder and partner, Arizona State University is at the forefront nationally and internationally in advancing research and discovery with:
Looking for an accelerated way to earn two powerful degrees and launch your international career? ASU London offers students a UK-accredited degree enhanced by the globally recognised curriculum of Arizona State University, ranked the #1 most innovative university in the US for 11 consecutive years (2016-2026) by U.S. News & World Report, with US master’s degree pathways integrated directly into your programme.
Accelerate your future and graduate with both a bachelor's and a master's degree in just 4 years, saving time and expense. And, your pathway to the US is guaranteed if you meet entry requirements.
Study across both the UK and US and double your career connections and prospects. If you want global opportunities for a career, this is your perfect place to start.
With practical, real-world learning and problem-solving to gain valuable professional skills, every ASU London degree is inspired by the university ranked #1 in the US for innovation by U.S. News & World Report for 11 years running.
Earn a degree shaped by innovation, technology, and AI, designed to better prepare you for the careers of today and the future.
Study in London. Study in the US. Earn two degrees and double your experience in two of the world’s most exciting places to learn and live.
Earn a master’s from Arizona State University and tap into over one million alumni, 650+ global industry partners - including EY, Amazon, Apple, Intel, Microsoft, NVIDIA, Boeing, and Goldman Sachs - plus strong UK collaborations for global career opportunities.
Accommodation guidance
Appeals, complaints and misconduct
Finance guidance
International student support
Welcome and induction
On-campus events
Signposting to job opportunities
Wellbeing
Counselling and mental health
Disability support/ learning success
Student feedback
UK Fees at ASU London
Bachelor of Computer Science:
UK & Ireland, full-time – £9,275 per year
International, full-time – £23,600 per year
Tuition fees cover the cost of your teaching, assessments, facilities and support services. There may be additional costs not covered by this fee such as re-assessments should you need them. Students will be required to have their own materials such as laptop, scientific calculator and stationery.
Yes. If you wish to study for more than one year in the US, you can apply to study additional specialisations and extend your study visa at Arizona State University.
In relation only to UK work rights, currently ASU London’s UKVI student sponsor license does not allow our sponsored international students to work in the UK, either during their studies or after they graduate.
This does not relate to post-study work rights in the US if you choose to continue your studies and complete your master’s degree at Arizona State University.
We are working towards full UKVI student sponsor status and will keep international applicants informed on progress. It is subject to ASU London continued UKVI compliance and subsequent approval from the UKVI. Once ASU London has UKVI full sponsor status:
Your enrolment advisor will keep you informed as to progress on this important information during your application process.
For more information on student visas and work rights, please visit our student visas page.
No. ASU London is an independent, UK accredited higher education institution with degree-awarding powers from the Office for Students. It is supported by Arizona State University and also partner Cintana Education.
ASU London provides UK students and international learners with the opportunity to study in one of the world’s best 3 best student cities (QS Best Student Cities 2026), while gaining access to internationally recognised postgraduate degrees from Arizona State University, ranked in the top 1% of all universities globally (CWUR 2025).
