Course overview
Conversion course
This Computer Science with Artificial Intelligence MSc is ideal if you’re new to computing and want to transition into the rapidly growing technology sector, with a particular focus on intelligent systems and data-driven technologies. If you’ve already studied computer science, we recommend exploring our Advanced Computer Science (Artificial Intelligence) MSc instead.
Learn the fundamentals of computer science, without needing any previous academic knowledge, and graduate qualified and ready for a challenging and rewarding career on the cutting-edge of technology.
Digital and AI skills are now essential across industries, from finance and healthcare to creative industries and public services. On this course, you’ll build a strong foundation in computer science while developing specialist knowledge in AI. This will give you the technical expertise, practical skills and confidence needed to pursue exciting careers in AI, data science, software development and intelligent systems.
You’ll learn through an intensive, hands-on approach that combines theory with practical learning. You will hone your programming expertise from first principles thinking, explore the workings of modern computer systems and networks, and develop a strong grounding in AI. As you progress, you’ll deepen your AI focus through specialist modules and project work aligned to your career ambitions.
We’ll also help develop your employability and applied AI expertise through real-world projects, industry-relevant technologies and responsible use of AI.
Your learning is informed by the School of Computer Science and backed by our strong roots in relevant research, so your teaching is current and shaped by the challenges we face today. When you graduate, you’ll have everything you need to thrive in an AI-driven economy.
Why study at Leeds?
- No experience necessary: Join a conversion programme that transitions you from a student with minimal experience to a confident, industry-ready computing professional within 12 months.
- A strong practical focus: Learn by doing through hands-on programming, real-world problem solving and project-based assessment, using industry-standard tools, workflows and development practices.
- Your course, your choice: Tailor your degree through specialist routes in AI or software engineering, alongside a broad pathway, allowing you to align your studies with emerging career opportunities.
- Gain industry-relevant skills: Get experience in areas such as cloud computing, software development, data management and networked systems, with the chance to engage with work-based learning, group projects or applied industry-style challenges.
- Engage with research-informed teaching: Learn from leading academics within the School of Computer Science, whose expertise spans AI, systems, software engineering and a range of digital applications.
- Build professional skills and industry insight: You can complete an eight-week optional online work experience programme, working on a real project with a partner organisation.
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Course details and modules
This MSc Computer Science with Artificial Intelligence is delivered over one year full-time and is designed to take you from foundational principles through to applied, career-focused expertise in intelligent systems. The programme is carefully structured so that you develop core computing knowledge first, before progressing to more specialised and applied areas of AI and data-driven technologies.
In the first semester, you will build essential skills in programming, computational thinking and computer systems, alongside gaining a grounding in AI, including its core concepts, applications and wider societal impact. This provides the foundation needed to engage confidently with more advanced AI techniques and applications.
In the second semester, you will deepen your knowledge through modules in areas such as databases, software engineering, web development and network security, while applying these within AI-focused contexts. You will further specialise in AI, developing practical experience in data-driven modelling, intelligent systems and real-world AI applications. A work-based learning or applied project component further enhances your professional skills and experience.
Over the summer, you will undertake a substantial individual research or industry-focused project, typically aligned with AI or data-driven technologies, allowing you to integrate and apply your knowledge to a real-world problem.
By the end of the programme, you will have developed strong programming ability, a solid foundation in computer science, and practical experience in designing and building AI-enabled systems. You will also gain skills in problem-solving, teamwork and professional practice, preparing you for a range of roles in the technology sector.
Through this programme, you will develop:
Knowledge of:
- core programming concepts, algorithms and data structures
- computer systems, networks and distributed/cloud computing
- software engineering principles, development lifecycles and tools
- data management, databases and data-driven technologies
- AI methods, including machine learning and intelligent systems
- ethical, societal and professional implications of AI
- contemporary trends and practices in AI and the wider technology sector
Skills in:
- designing, implementing and evaluating AI-enabled software systems
- applying machine learning and data-driven approaches to real-world problems
- problem-solving using computational thinking, abstraction and modelling
- analysing system and model performance, making informed technical decisions
- working with modern tools and frameworks used in AI and software development
- communicating technical and AI concepts effectively to different audiences
- applying knowledge in real-world, industry-relevant AI contexts
Professional behaviours including:
- collaborative working and teamwork in technical and interdisciplinary environments
- independent learning and adaptability in a rapidly evolving AI landscape
- ethical and responsible development and use of AI
- project planning, organisation and reflective practice
- awareness of professional standards, emerging technologies and industry expectations in AI and computing
Course structure
The list shown below represents typical modules/components studied and may change from time to time. Read more in our terms and conditions.
Year 1 compulsory modules
Fundamentals of Programming - 30 credits
This module introduces the fundamentals of programming and software development for learners with little or no prior experience. You will develop core programming skills using a modern language such as Python, alongside computational thinking techniques to break down problems and design structured solutions. You will also learn how to represent and communicate ideas using tools such as pseudocode and flowcharts.
The module also explores essential algorithms and data structures, including lists, stacks, queues and trees, and introduces methods for comparing their performance and understanding trade-offs. Emphasis is placed on good software design through abstraction, decomposition and modular development, as well as exposure to industry-standard tools such as version control (e.g. Git) and development environments.
Computer Systems - 15 credits
This module introduces the fundamental principles that underpin how computer systems operate, from low-level hardware to modern networked and cloud-based environments. You will explore how data is represented and processed within a computer, alongside key concepts in computer architecture such as processors, memory, storage and instruction execution.
The module also covers the basics of computer networks and distributed systems, including network structures, protocols and common services such as DNS and DHCP. You will gain an understanding of how systems are designed and deployed in modern contexts, including cloud computing technologies such as virtual machines and containers, while developing an awareness of performance considerations and trade-offs in hardware and system design.
Practical Application of Artificial Intelligence - 15 credits
This module provides an accessible introduction to artificial intelligence (AI), focusing on its practical applications in the modern world. You will explore what AI is, how it has developed over time, and the different types of AI systems in use today, building an understanding of how intelligent technologies are designed and applied across a range of domains.
The module also examines the real-world impact of AI, including its use in areas such as automation, decision-making and data-driven services. Alongside this, you will consider the ethical, societal and professional challenges associated with AI, developing an informed and responsible perspective on its role in shaping the future.
Project - 60 credits
This module forms the culmination of the programme, providing you with the opportunity to undertake an in-depth, independent project on a substantial computing problem. You will apply the knowledge and skills developed throughout the course to design, implement and evaluate a solution, often aligned to your career interests or a real-world challenge.
The project emphasises independent learning, critical thinking and professional practice. You will plan and manage your work, engage with relevant literature or technologies, and produce a significant piece of technical work alongside a written report. This enables you to demonstrate your technical competence, problem-solving ability and readiness for employment in the technology sector or further study.
Database and Data management - 15 credits
This module introduces the core principles of data management and database systems, focusing on how data is organised, stored and accessed in modern applications. You will learn how to design and interact with databases, gaining practical experience of structuring data effectively and ensuring its integrity and reliability.
The module also explores key concepts such as data modelling, querying and managing relational databases, alongside an introduction to broader data management practices. You will develop an understanding of how data is used within software systems, the importance of efficient data handling, and the role of databases in supporting real-world applications across a wide range of domains.
Artificial Intelligence - 15 credits
This module introduces the core principles and techniques of artificial intelligence, focusing on how intelligent systems are designed, implemented and applied in real-world contexts. You will explore key areas such as machine learning, data-driven modelling and intelligent decision-making, developing an understanding of how AI systems learn from data and are used to solve complex problems.
The module emphasises practical application, giving you hands-on experience of working with AI tools and techniques to analyse data, build simple models and evaluate their performance. You will also examine the limitations, risks and ethical considerations associated with AI, enabling you to critically assess its impact and apply it responsibly across a range of domains.
Year 1 optional modules (selection of typical options shown below)
You will choose two optional modules as part of your degree. The modules listed below are examples of the options typically available from the School of Computer Science. You will also have the opportunity to select modules from across the University, allowing you to practice your computer science skills while also developing expertise in specific specialist areas.
Software Engineering - 15 credits
This module introduces the key principles and practices of modern software engineering, focusing on how reliable, maintainable and scalable software systems are designed and developed. You will explore the full software development lifecycle, from requirements gathering and system design through to implementation, testing and deployment.
The module emphasises collaborative and professional ways of working, including version control, code review, documentation and iterative development approaches such as agile methods. You will gain practical experience of building software as part of a team, while developing an understanding of quality assurance, testing strategies and best practices that underpin effective software engineering in industry.
Network Security and Defensive Practices - 15 credits
This module introduces the fundamental concepts and practices of network security, focusing on how computer systems and networks are protected against threats. You will explore common vulnerabilities, attack methods and defensive techniques, alongside the principles of secure system design and risk management.
The module also examines practical security measures such as network monitoring, access control and secure communication protocols. You will develop an understanding of how defensive strategies are implemented in real-world environments, and gain awareness of the trade-offs between security, performance and usability in modern computing systems.
Web Development - 15 credits
This module introduces the principles and practices of modern web development, focusing on how interactive and user-friendly websites and web applications are designed and built. You will gain an understanding of how the web works, alongside practical experience in developing front-end interfaces and basic back-end functionality.
The module explores core web technologies, including structuring content, styling interfaces and implementing dynamic behaviour. You will also consider key aspects of usability, accessibility and performance, developing the skills to create responsive, well-designed web applications that meet real-world user and industry expectations.
Work-based Learning - 15 credits
This module provides an opportunity to apply your developing technical skills within a real-world or professionally relevant context. You will engage in practical, work-related learning activities such as industry-style projects, placements or collaborative challenges, enabling you to bridge the gap between academic study and professional practice.
The module emphasises the development of employability skills, including teamwork, communication, problem-solving and project management. You will gain experience of working to real-world requirements, reflecting on your performance and developing an understanding of professional standards, workplace expectations and career pathways within the technology sector.
Enhance your academic and subject-specific language
As part of your course, you will have access to the Professional and Academic Communication module, which provides valuable insights into studying a postgraduate degree in the UK while helping you develop your academic and subject-specific vocabulary.
Through a combination of in-person workshops and independent online study, you will explore the use of technology — such as translation tools and generative AI — to support effective communication. You will also build the language and literacy skills necessary to become a more confident and capable communicator throughout your studies.
Learning and teaching
You will learn through a combination of lectures, interactive workshops, practical lab sessions and small-group activities, supported by online resources and guided independent study. Teaching is highly applied, with a strong emphasis on hands-on programming, problem-solving and project-based learning, ensuring you develop practical skills alongside theoretical understanding. Digital learning technologies are embedded throughout the programme, including coding platforms, virtual labs and collaborative tools that reflect modern industry practice.
The programme adopts an active and inclusive approach to learning, designed to support students from a wide range of academic backgrounds. Teaching is structured to build confidence progressively, with clear guidance, regular feedback and opportunities to engage in collaborative learning. Group work, peer interaction and supported practical sessions help foster a strong sense of belonging within your course peers, enabling you to learn from both staff and fellow students.
Your learning is informed by sector-leading approaches in computer science education, integrating research-informed content with current industry practices such as agile development, version control and modern software tools. You will engage in a blend of face-to-face teaching and technology-enhanced learning, creating a flexible, engaging and supportive learning experience that prepares you effectively for further study or a career in the technology sector.
Facilities
You can access a range of modern, purpose-built computing facilities within the School of Computing at Leeds. Teaching takes place in dedicated computer laboratories equipped with high-specification machines and industry-standard software, enabling you to develop practical skills in programming, software development, data analysis and systems design.
Specialist labs support learning in core areas such as networks, systems and security, providing hands-on experience with contemporary technologies and environments. You will also have access to virtualised and cloud-based platforms, reflecting current industry practice in distributed computing and cloud infrastructure.
Programme team
On this course, you’ll be taught by our expert academics, from lecturers through to professors. You may also be taught by industry professionals with years of experience, as well as trained postgraduate researchers, connecting you to some of the brightest minds on campus.
Assessment
You will undergo assessment through a diverse range of methods designed to reflect real-world computing practice and support different learning styles. These include practical programming tasks, coursework assignments, group projects, technical reports, presentations and your final MSc project. Many assessments allow you to select or shape topics aligned with your interests or career goals, enabling you to engage more deeply with areas that matter to you.
Your assessments focus strongly on authentic tasks that mirror professional practice in the technology sector. You will design and build software, analyse data, evaluate systems and communicate technical solutions, developing transferable skills such as problem-solving, critical thinking, collaboration and project management. These approaches ensure you graduate with both technical expertise and the ability to apply it effectively in real-world contexts.
Throughout the programme, you will be supported in developing your ability to critically evaluate information, draw on evidence from multiple sources and engage with contemporary issues such as ethics, security and emerging technologies. Your assessments aim to encourage reflection, conceptual understanding and the integration of knowledge across different modules.
We are committed to fair and inclusive assessment. We’ll use a variety of assessment formats to ensure you have the chance to demonstrate your strengths and are supported by clear guidance, marking criteria and regular feedback. Flexible approaches are embedded where appropriate, ensuring assessments are meaningful, accessible and engaging, and that they support your development as a confident and capable computing professional.
Applying
Entry requirements
A Bachelor degree with a 2:1 (hons) in any subject that is not computer science.
You will also need to demonstrate appropriate mathematical competence. This requirement may be met through successful completion of a mathematics module within a Bachelor degree, attainment of a minimum grade at secondary education level, for example, a GCSE Mathematics at grade 5 (C) or an equivalent qualification.
We encourage you to apply if you have a 2:2 (hons) and relevant work experience or professional qualifications. We take a flexible, inclusive approach and consider every application carefully, although we can’t guarantee an offer.
If you have a Computer Science background, you may be interested in studying one of our Advanced Computer Science programmes.
We accept a range of international equivalent qualifications.
English language requirements
IELTS 6.5 overall, with no less than 6.0 in any component. For other English qualifications, read English language equivalent qualifications.
Improve your English
International students who do not meet the English language requirements for this programme may be able to study our postgraduate pre-sessional English course, to help improve your English language level.
This pre-sessional course is designed with a progression route to your degree programme and you’ll learn academic English in the context of your subject area. To find out more, read Language for Engineering (6 weeks) and Language for Science: Engineering (10 weeks).
We also offer online pre-sessionals alongside our on-campus pre-sessionals. Find out more about our six week online pre-sessional and our 10 week online pre-sessional.
You can also study pre-sessionals for longer periods – read about our postgraduate pre-sessional English courses.
How to apply
Please see our How to Apply page for information about application deadlines.
The ‘Apply’ link at the top of this page will take you to information on applying for taught programmes and to the University's online application system.
If you're unsure about the application process, contact the admissions team for help.
Documents and information you'll need
- a copy of your degree certificate and transcript, or a partial transcript if you’re still studying
- contact details for two academic references
- a personal statement
- an up-to-date CV
- your approved English Language test* (if applicable)
- a letter of sponsorship, if you need one
* Applicants who have not yet completed an approved English language test may apply for a Masters course prior to taking a test.
Read about visas, immigration and other information in International students. We recommend that international students apply as early as possible to ensure that they have time to apply for their visa.
Admissions policy
University of Leeds Admissions Policy 2027
This course is taught by
Contact us
Postgraduate Admissions team
Email: pgcomp@leeds.ac.uk
Fees
UK: £14,700 (Total)
International: £34,600 (Total)
Read more about paying fees and charges.
Additional cost information
There may be additional costs related to your course or programme of study, or related to being a student at the University of Leeds. Read more on our living costs and budgeting page.
Scholarships and financial support
If you have the talent and drive, we want you to be able to study with us, whatever your financial circumstances. There may be help for students in the form of loans and non-repayable grants from the University and from the government. Learn more about Masters funding.
Scholarships are also available to help fund your Masters. Find out more and check your eligibility below:
Career opportunities
As a graduate of this course, you’ll be well prepared to enter a wide range of roles within the rapidly growing technology sector, particularly in areas driven by AI and data. The programme develops both the technical expertise and professional skills sought by employers across industries, enabling you to pursue careers in areas such as AI, machine learning, data science and intelligent systems.
Where this degree could take you
Typical job roles that you could find work as include:
- data analyst or junior data scientist
- AI or machine learning engineer (entry-level)
- AI developer or intelligent systems engineer
- IT consultant or technology analyst
The skills you’ll develop on this programme are highly transferable, meaning you’ll also be well placed to work across a wide range of industries, including finance, healthcare, retail, government, education, creative industries and digital start-ups. A key advantage of this conversion degree is the ability to combine your existing academic background with newly acquired AI and computing expertise. This enables you to work at the intersection of AI and your original discipline. For example, you could apply AI in areas such as fintech, digital health, business analytics, creative technologies or public policy, an increasingly valuable skill in today’s data-driven, AI-enabled economy.
The programme’s strong emphasis on practical learning, industry-relevant tools and real-world projects ensures that you graduate with the experience and confidence to contribute effectively in professional environments. The final MSc project further enables you to demonstrate your expertise in AI or a related specialism, providing a valuable piece of work to showcase to potential employers.
For those interested in further study, the programme also provides a solid foundation for progression to more specialised postgraduate study or research in AI, data science and related areas of computer science.
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Careers support
At Leeds, we help you to prepare for your future from day one. We have a wide range of careers resources — including our award-winning Employability Team, who are in contact with many employers around the country and advertise placements and jobs. They are also on hand to provide guidance and support through the whole job application process, ensuring you are prepared to take your next steps after graduation and get you where you want to be.
- Qualified careers consultants: Gain guidance, support and information to help you choose a career path. You’ll have access to 1-2-1 meetings and events to learn how to find employers to target, write your CV and cover letter, research before interviews and brush up on your interview skills.
- Employability and networking events: We run a full range of events, including careers fairs and industry talks in specialist areas and across broader industries, with employers who are actively recruiting for roles, giving you the opportunity to network and engage with industry sponsors.
- Employability skills training: To support your transition to the workplace, we embed training in a range of key transferable skills valued by employers, such as team working and presentation skills, in all our programmes.
- MyCareer system: On your course and after you graduate, you’ll have access to a dedicated careers portal where you can book appointments with our team, get information on careers and see job vacancies and upcoming events.
- Joblink: A student job shop offered by our Leeds University Union (LUU), designed to link students with local employers who provide rewarding work experience. LUU also offers volunteering opportunities and over 300 clubs and societies to get involved in.
Explore more about your employability opportunities at the University of Leeds:
Find out more about career support.
Work placements and industry experience
While studying at Leeds, you’ll have the opportunity to complete an eight-week work experience programme working on a project aligned with your academic discipline in partnership with a relevant organisation.
You’ll develop key professional skills and gain valuable insight into your chosen field, helping to solve a real business challenge based on a live company brief.
This experience will enhance your CV, helping you stand out in the competitive graduate jobs market and improving your prospects of securing the career you want.
Benefits of the virtual work experience:
- Fully online and designed to fit around your studies.
- Opportunities to build your professional network.
- Gain valuable insight and consultancy experience with a UK or international organisation, working on a time-limited brief.
- Collaborate in multidisciplinary teams to tackle real business challenges.
- Apply your learning in practice and develop hands-on skills.
- Strengthen your employability and career prospects.
- Build confidence, make new connections and explore your future career options.
Throughout the eight-week programme, you’ll be supported by an academic tutor who will meet regularly with your group. You’ll also receive guidance from the employability team at every stage.
We’ll provide tailored careers support sessions to help you develop professional behaviours and showcase your skills to employers. On completion, you’ll receive a reference letter from Leeds recognising the skills and experience you have gained.
When you begin your MSc, the employability team will introduce the scheme during a lecture in your first month, answer any questions and explain how to register.