What You Need to Know Before
You Start
Starts 7 June 2026 09:54
Ends 7 June 2026
4 hours 59 minutes
Optional upgrade avallable
Not Specified
Progress at your own speed
Paid Course
Optional upgrade avallable
Overview
This course is an introduction to Creative AI, a growing field at the intersection of machine learning and artistic practice. During the course, you’ll learn how neural networks work, how they are trained, and how they can be applied.
Exploring how artificial intelligence can be used as a transformative tool across a variety of creative practices. By the end of this course you will be able to:
- Understand the core principles of artificial intelligence and how they apply within creative contexts, including visual art, design, music, and performance. - Identify the roles of neural networks and machine learning in creative AI systems, and recognise how artists are using these tools in practice. - Reflect critically on the ethical, legal, and cultural implications of working with AI, including questions of authorship, bias, and creative agency. - Experiment with basic AI tools and techniques, developing an informed and hands-on understanding of how generative systems can support co-creative processes.
Through hands-on coding exercises and guided walkthroughs, you’ll train your first AI model and gain a practical understanding of how machine learning functions beneath the surface. Alongside technical skills, the course also invites you to reflect on broader issues:
What does it mean to create with AI?
How is AI changing authorship, labour, and the creative industries? What ethical concerns arise when training models on existing cultural data?
Featuring insights from leading AI artists, researchers, and technologists, this course will give you both the technical foundation and critical perspective to begin working with AI in your own creative practice. No prior coding experience is required, just curiosity and a willingness to experiment.
Syllabus
- Introduction to Creative AI
- Build your first AI model
Taught by
Terence Broad
Subjects
Computer Science