University of the Arts London
Public University • UK
Showing 6 courses from University of the Arts London
Fashion Values: Society
University of the Arts London (via Coursera)
Fashion and society are deeply intertwined through everyday actions, behaviours and business models, and can be both empowering and exploitative. On this course from London College of Fashion's Centre for Sustainable Fashion, you’ll explore how fashion can paradoxically be a force for societal good, creating agency, collaboration, dignity and distinction between people, or a cause and perpetuator of injustice. Social injustice in and through fashion is experienced widely and can perpetuate inequality and exploitation. By the end of this course you’ll understand how activism can be used to challenge this and be inspired by intersectional perspectives from activists around the world, learning from historical and contemporary case studies and resources. You’ll explore the process of change in relation to fashion and society, exploring various models that provide ways of thinking, feeling or working towards change. You’ll learn about where power lies to create change and to challenge social injustice in fashion. You’ll examine many approaches to and models of activism, as well as the importance of resilience. Use design thinking to develop fashion activities and behaviours that contribute to social justice You’ll be supported through the design thinking process to define a specific problem and generate ideas in response to the question: ‘How will we use fashion activism to challenge social injustice?’
Fashion Values: Nature
University of the Arts London (via Coursera)
Join Centre for Sustainable Fashion and understand biodiversity in the context of fashion, creating a plan for fashion that protects Earth’s ecosystems. Discover fashion practices that can protect, restore, and regenerate ecosystems: Nature is the life force that provides us with the air, water, soil, and minerals that sustain life on earth. These elements come together in the clothes we wear. This course will help you build the knowledge, skills, and connections to reimagine fashion’s practices and develop a plan to put nature first. You’ll join a community of fashion and sustainability thinkers and doers that have the vision, skills, and commitment to radically transform how we live and work through fashion. Explore the impact of fashion on biodiversity and earth’s systems: With more than one million species of plants and animals at risk of extinction, our ecosystems are under stress. Fashion plays a direct role in this, and on this course you’ll identify how dominant damaging systems of fashion production and consumption can be transformed to protect natural life on our planet. Use design thinking to radically rethink fashion products, services, and systems: Very few fashion companies have biodiversity strategies, but you’ll examine the tools and frameworks used by companies who are developing a nature-centred way of working. You’ll also be set a design thinking challenge, asking you to develop a fashion product, service or system which supports the restoration and regeneration of nature. Respond to sustainability challenges with Centre for Sustainable Fashion: This course is led by fashion and sustainability experts from Centre for Sustainable Fashion and shares knowledge from world-leading fashion practitioners and researchers. With over 110,000 learners engaged to date, you’ll gain valuable insights from fellow fashion and sustainability changemakers from around the world.
Creative AI: Text and Transformations
University of the Arts London (via Coursera)
This course explores how artificial intelligence is reshaping the way we write, read, and engage with language. Focusing on generative text models, creative writing, and critical perspectives, you’ll learn how language models are trained, how artists and writers are using them in practice, and what social, ethical, and cultural questions they raise. By the end of the course you will be able to: Explore how AI can generate and manipulate language using tools like RNNs, LSTMs, and large language models such as GPT. Understand how machine learning systems represent meaning, similarity, and structure in text through vector spaces and model training. Evaluate the social and ethical implications of language models, including disinformation, bias, surveillance, and the future of authorship. Experiment with code-based and web-based tools for generating text, and reflect on how AI might expand or challenge your own writing practices. Through creative walkthroughs, coding demos, and critical discussions, you’ll learn how language models function, reflect on how they relate to broader histories of text production, and examine the cultural impact of machine-generated language in media, publishing, and online discourse. Featuring insights from leading researchers, technologists, and experimental writers, this course provides both the conceptual grounding and practical tools to begin working with AI in your own creative text-based projects. No coding experience is required, just curiosity and a desire to explore new forms of writing and expression.
Creative AI: Images and Media
University of the Arts London (via Coursera)
This course explores how artificial intelligence is transforming the way we create, interpret, and engage with images and visual media. Focusing on generative tools, datasets, and cultural impact, you’ll learn how AI systems are trained to generate images, how artists are using them creatively, and what ethical, legal, and political questions arise as a result. By the end of the course you will be able to: Explore how AI can be used to generate and manipulate images using techniques like GANs, CLIP, and diffusion models. Understand the impact of datasets on the aesthetics and biases of generative AI, and how dataset design influences creative output. Evaluate the ethical and legal implications of AI image-making, including issues of consent, appropriation, and authorship. Experiment with text-to-image tools and other generative systems, gaining insight into how artists are working with AI in practice. Through hands-on activities, creative walkthroughs, and interviews with artists and researchers, you’ll investigate how generative systems work, reflect on how they relate to earlier image-making technologies like photography, and examine the social debates surrounding AI art platforms and dataset ethics. Featuring perspectives from leading artists and technologists working at the cutting edge of AI and visual culture, this course provides both the technical understanding and critical insight to begin experimenting with AI in your own creative media practice. No technical experience is required, just curiosity and a willingness to engage with new visual tools and ideas.
Creative AI: Sound, Music and Interaction
University of the Arts London (via Coursera)
This course explores how artificial intelligence is reshaping the way we make, perform, and think about music. Focusing on sound, interaction, and creative collaboration, you’ll learn how AI can be used to build new kinds of musical instruments, act as a creative partner, and generate original audio and voice. By the end of the course you will be able to: Explore how AI can be used to design new musical instruments and interactive systems that respond to gesture, movement, and sound. Understand the role of AI as a creative partner in music composition and performance, and examine how this reshapes ideas of creativity and authorship. Evaluate the ethical and legal implications of using AI in music, including issues around ownership, attribution, and the rights of artists and performers. Experiment with practical tools for generating, manipulating, and performing music using AI, gaining insight into current techniques and future possibilities. Through hands-on walkthroughs, practical tools, and case studies, you’ll experiment with gesture-based systems, explore real-time music generation, and discover how machine learning can be trained to respond to human input. Alongside these technical explorations, the course invites you to engage with critical questions around creativity, authorship, and the legal implications of AI in music production. Featuring perspectives from leading artists, choreographers and researchers working at the intersection of AI and music, this course provides both the practical knowledge and critical framework to begin experimenting with sound and AI in your own creative practice. No prior technical experience is required, the course has been designed for anyone with a curiosity and a passion for exploring new ways of making music.
Introduction to Creative AI
University of the Arts London (via Coursera)
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.