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Data Science and AI in Creative Industries at Norwich University of the Arts - UCAS

Course options

2025 - 2026
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There are other course options available which may have a different vacancy status or entry requirements – view the full list of options

This course is subject to validation. You can still apply for this course while it is being approved.

Course summary

Learn how computer science, data analytics, and AI drive innovation and enhance everyday experiences in the creative industries. The MSc in Data Science and AI in Creative Industries builds on your experience in creative and non-technical subjects to prepare you for professional roles in the rapidly evolving fields of creative technology, data science and AI. This course takes an experimental and exploratory approach, enabling you to investigate fundamental conceptual and technological frameworks. You will engage with a range of computational approaches to data science questions, using your specialist knowledge to interrogate and redefine the boundaries of data science and AI, presenting innovative solutions based on experimental research data and methods. This course is for those looking to break into data science and AI from non-technical backgrounds. The course focuses on tackling complex data science problems within creative technology and functional AI. Through project-based learning, you will enhance your skills in modern programming languages, machine learning methods, experimental tools, and data analysis. The course supports a critical and ethical approach, reflecting on the social implications of data science and AI on society. There is an emphasis on interdisciplinary collaboration and creative problem-solving to strengthen your technical and teamwork skills, critical thinking, and your proficiency in analysing, validating, and interpreting data. Why study with us

  • Advanced technical skills: Develop your expertise in modern programming languages, machine learning methods, experimental tools, and data analysis, creating sophisticated, clean, and efficient solutions.
  • Interdisciplinary approach: Benefit from shared delivery with other postgraduate courses, fostering a collaborative environment that reflects industry practices and promotes knowledge-sharing and interdisciplinary interaction.
  • Professional-level resources: Utilise a wide range of professional resources, including contemporary technology and industry-standard tools, media labs, 2D & 3D studios, workshops, computer labs, high-specification PCs, digital darkrooms, analogue and digital resources, licensed specialist software, a media resource centre, and the Make Space, supporting you in creating practical and creative solutions to project briefs.
  • Ethical and inclusive research: Adopt an ethical approach to your work, focusing on the social and ethical implications of data science and AI, and emphasising accessibility, equality, diversity, and sustainability.
  • Professional portfolio development: By the end of the course, you will have created a professional body of work that reflects your interests and prepares you for industry, enhancing your ability to communicate research visually.
  • Innovative problem solving: Engage with complex computational problems through project-based learning, promoting original and innovative approaches to technical proficiency and professional working methods.
Course structure This course is part of our suite of Master’s in Computing, Games and Data Science, offering a collaborative framework across various specialisations, also including MSc Creative Computing and MSc Games Computing. This provides students with opportunities to engage with peers from different disciplines while working on individual assignments. Such collaboration mirrors the professional dynamics in the creative industries today, allowing students to gain valuable experience in interdisciplinary teamwork and real-world problem-solving. This programme is a one-year course, including 30 weeks of direct teaching time and a 15-week final project. You will need to complete five units and one 60-credit major project (180 credits in total). All units on the course are compulsory and must be passed in order to complete the award. If you study part-time your modules will be split across two years.

Assessment method

Our assessment methods will vary based on the unit you choose and provide a comprehensive measure of your learning and progress. More information can be found at https://norwichuni.ac.uk/msc-data-science-and-ai-in-creative-industries/#assessment

Entry requirements

We typically require an honours degree of 2:1 or equivalent in art and design, computer science, or humanities. The most relevant undergraduate degrees are in digital media – graphic design, communication design, interactive media, information technology – but also psychology and ethnography. Those with industry experience or relevant skills from non-traditional backgrounds are encouraged to apply, including individuals currently employed. If you’re unsure about your eligibility, please contact us for guidance before applying.

English language requirements

If English is not your first language, IELTS 6.5 (or equivalent) is required, with a minimum of 5.5 in reading, writing, listening, and speaking.

Fees and funding

Tuition fees

England £9600* Whole course
Northern Ireland £9600* Whole course
Scotland £9600* Whole course
Wales £9600* Whole course
Channel Islands £9600* Whole course
Republic of Ireland £9600* Whole course
EU £18000* Whole course
International £18000* Whole course

*This is a provisional fee and subject to change.

Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .

Additional fee information

These provisional fees are based off the 2024/25 fees and are subject to change.
Data Science and AI in Creative Industries at Norwich University of the Arts - UCAS