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⇱ Creative AI: Images and Media | Coursera


Creative AI: Images and Media

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Creative AI: Images and Media

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Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

9 hours to complete
Flexible schedule
Learn at your own pace

Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

9 hours to complete
Flexible schedule
Learn at your own pace

There are 3 modules in this course

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.

In this module, we’ll explore how AI can be used to generate images using a type of algorithm called a Generative Adversarial Network (GAN). We’ll highlight artists who have created work with GANs and examine how these tools are shaping contemporary creative practices. Alongside this, we’ll draw parallels between the history of photography and the rise of generative AI, considering how both technologies have transformed image-making and influenced the course of art history.

What's included

4 videos9 readings1 assignment2 discussion prompts1 ungraded lab

4 videosTotal 16 minutes
  • As uncanny as a body3 minutes
  • Preserving cultural practices with AI art5 minutes
  • Media ecologies4 minutes
  • Generative AI and art history3 minutes
9 readingsTotal 75 minutes
  • Introduction to generating images with AI5 minutes
  • The GAN algorithm 5 minutes
  • Real or fake money?5 minutes
  • GAN training10 minutes
  • Introducing StyleGAN and deepfakes10 minutes
  • What is latent space?10 minutes
  • Artists working with GANs10 minutes
  • The changing media/technology landscape10 minutes
  • Module 1 Summary10 minutes
1 assignmentTotal 30 minutes
  • Generative AI's impact on art30 minutes
2 discussion promptsTotal 20 minutes
  • Does your DoppleGANner resemble you?10 minutes
  • Share your favourite artists working with AI10 minutes
1 ungraded labTotal 60 minutes
  • Code Walkthrough: Latent space60 minutes

In this module, we’ll focus on how image datasets for AI are made, and explore the political and legal issues that arise from their creation. We’ll examine how these practices impact creative practitioners, consider how artists are engaging with AI, and discuss the legal challenges facing large AI art platforms.

What's included

7 videos8 readings1 assignment1 discussion prompt

7 videosTotal 36 minutes
  • Breaching Copyright6 minutes
  • Are there legal risks to AI tools?4 minutes
  • Protections for artists7 minutes
  • Does this artwork breach copyright?5 minutes
  • The role of artists making datasets2 minutes
  • Making datasets for creative projects6 minutes
  • Ethics of making datasets6 minutes
8 readingsTotal 75 minutes
  • The emergence of AI art platforms5 minutes
  • The backlash against AI art10 minutes
  • Lawsuits against AI art and tech platforms10 minutes
  • Protecting your work from generative AI10 minutes
  • Watch Blade Runner: auto encoded10 minutes
  • The legal concepts of fair use and fair dealing 10 minutes
  • Artists who make their own dataset10 minutes
  • Module 2 summary10 minutes
1 assignmentTotal 30 minutes
  • AI image datasets and consent30 minutes
1 discussion promptTotal 10 minutes
  • Your thoughts on Blade Runner: auto encoded10 minutes

In this final module of the course, we’ll take an in-depth look at text-to-image AI systems, which have risen rapidly in popularity in recent years. We’ll hear from artists and researchers who have worked extensively with these tools, using their projects as a lens to understand the creative and artistic implications of text-to-image generation. You’ll also take part in a practical activity reimagining animation using text-to-image techniques, inspired by the work of artist Adam Cole.

What's included

5 videos8 readings1 assignment1 discussion prompt1 ungraded lab

5 videosTotal 25 minutes
  • What is prompt engineering?4 minutes
  • The story of Twitter artbot4 minutes
  • The story of Kiss/Crash6 minutes
  • AI art and readymade4 minutes
  • Historical parallels of generative art7 minutes
8 readingsTotal 80 minutes
  • Associating text and images10 minutes
  • Generating images from text10 minutes
  • Generative Art on Twitter 10 minutes
  • Kiss/Crash10 minutes
  • Reimagining animation with diffusion models10 minutes
  • The future of video generation10 minutes
  • Parallels with art history10 minutes
  • Future of AI art 10 minutes
1 assignmentTotal 30 minutes
  • Comparing text and image pairs30 minutes
1 discussion promptTotal 10 minutes
  • Discuss your outcome10 minutes
1 ungraded labTotal 60 minutes
  • Code walkthrough: stable diffusion60 minutes

Instructor

University of the Arts London
4 Courses1,680 learners

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