Introduction to Creative AI
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There are 2 modules in this course
This course is an introduction to Creative AI, a growing field at the intersection of machine learning and artistic practice. During the course, youβll 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, youβll 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.
This module introduces the field of Creative AI, offering a foundational overview of what AI is and how it intersects with creative practice. Youβll also meet the group of contributing experts whose work and perspectives will shape the discussions throughout this course.
What's included
6 videos6 readings1 assignment3 discussion prompts
6 videosβ’Total 37 minutes
- Meet the course contributors β’5 minutes
- AI & creative practice β’8 minutes
- The impact of AI on art β’6 minutes
- The impact of AI on employmentβ’5 minutes
- What trends excites you about AI?β’6 minutes
- What concerns you about AI?β’7 minutes
6 readingsβ’Total 27 minutes
- Welcome to the courseβ’5 minutes
- What is Creative AI?β’5 minutes
- What will you learn in these courses?β’5 minutes
- Timeline of Creative AIβ’5 minutes
- The impact of AI on creativity β’5 minutes
- Recap and preparation for Module 2β’2 minutes
1 assignmentβ’Total 30 minutes
- Reflection on AI & creativity β’30 minutes
3 discussion promptsβ’Total 30 minutes
- Share your creative practiceβ’10 minutes
- Are you worried about AI affecting your employment?β’10 minutes
- What trends in AI are most exciting or concerning to you?β’10 minutes
During this module we will talk through the steps of building our first AI model in the deep learning library PyTorch. We will talk about what a neural network is and how they are trained on data. We will then talk you through where to get started for continuing your journey with CreativeAI and introduce the three courses that follow this introductory course.
What's included
1 video13 readings1 assignment1 discussion prompt1 ungraded lab
1 videoβ’Total 6 minutes
- Getting started with Creative AIβ’6 minutes
13 readingsβ’Total 90 minutes
- Neural networks introductionβ’5 minutes
- Data as numbersβ’10 minutes
- Making predictions on dataβ’5 minutes
- How neural networks learnβ’10 minutes
- Supervised learning: Is it a cat or a dog?β’5 minutes
- Supervised learning: Rate this dog!β’5 minutes
- Regression and classification β’5 minutes
- Introduction to Google Collabβ’10 minutes
- How training works in PyTorchβ’10 minutes
- What can you do with CreativeAI?β’5 minutes
- Where to get started working with AIβ’5 minutes
- Creative AI coursesβ’10 minutes
- Summary and next stepsβ’5 minutes
1 assignmentβ’Total 10 minutes
- AI with PyTorch Summary Assignmentβ’10 minutes
1 discussion promptβ’Total 10 minutes
- What other tasks may be done with regression or classification?β’10 minutes
1 ungraded labβ’Total 60 minutes
- Code walkthrough: WeRateDogs Part 1β’60 minutes
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