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Terence Broad

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.

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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.

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What's inside

Syllabus

Making images with AI
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.
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Career center

Learners who complete Creative AI: Images and Media will develop knowledge and skills that may be useful to these careers:
Artificial Intelligence Artist
As an Artificial Intelligence Artist, you directly engage with cutting-edge technology to create compelling visual works. This course directly equips you with the understanding and practical skills to excel in this emerging field. You will explore how artificial intelligence can be used to generate and manipulate images using techniques like GANs and text-to-image diffusion models, gaining hands-on experience. The course examines how other artists leverage these tools creatively and critically, providing inspiration and practical insights for your own artistic practice. Furthermore, the focus on evaluating ethical issues such as consent, appropriation, and authorship in artificial intelligence image-making is crucial for developing a responsible and impactful artistic voice. This deep dive into generative systems, coupled with reflections on its historical precedents, helps build a foundational understanding of artificial intelligence's transformative role in contemporary art.
Generative Media Designer
As a Generative Media Designer, you create innovative visual content across various platforms, leveraging the power of artificial intelligence. This course provides a comprehensive foundation for this dynamic career, allowing you to explore how artificial intelligence transforms the creation and engagement with images and visual media. You will gain practical experience with generative tools, including text-to-image systems, and delve into how artists are using them creatively. A key aspect is understanding the impact of datasets on the aesthetics and biases of generative artificial intelligence, and how dataset design influences creative output, which is vital for producing ethically sound and visually resonant designs. The course also addresses the ethical and legal implications, such as issues of consent and authorship, which are increasingly relevant for professional media design.
Creative Technologist
A Creative Technologist bridges the gap between artistic vision and technical execution, often experimenting with innovative technologies. This course is highly relevant, providing both the technical understanding and critical insight to begin experimenting with artificial intelligence in creative media practice. You will explore how artificial intelligence can generate and manipulate images using techniques like GANs and diffusion models, gaining hands-on experience with text-to-image tools. Understanding how artists are working with artificial intelligence in practice will inspire innovative applications. The course's focus on evaluating ethical, legal, and political questions arising from artificial intelligence image-making, including consent and appropriation, equips you to navigate the complexities of integrating artificial intelligence into new creative projects responsibly. This blend of practical application and critical reflection is central to the role.
Ethical Artificial Intelligence Consultant
As an Ethical Artificial Intelligence Consultant, you guide organizations in developing and deploying artificial intelligence responsibly. This course is highly relevant, providing deep insight into the ethical, legal, and political questions that arise from artificial intelligence image-making. You will learn to evaluate fundamental issues such as consent, appropriation, and authorship in generative artificial intelligence, which are crucial for advising clients effectively. A strong focus on the impact of datasets on the aesthetics and biases of generative artificial intelligence, and the practices and politics of making datasets, directly informs strategies for mitigating harm and promoting fairness. This understanding of social debates surrounding artificial intelligence art platforms and dataset ethics provides a robust framework for an Ethical Artificial Intelligence Consultant. This role often requires an advanced degree.
Prompt Engineer
As a Prompt Engineer, your expertise lies in meticulously crafting text inputs to guide generative artificial intelligence models in producing specific, high-quality visual outputs. This course offers direct and invaluable experience for this role, providing an in-depth look at text-to-image artificial intelligence systems, which have risen rapidly in popularity. You will take part in practical activities experimenting with text-to-image tools, gaining insight into how artists and researchers work extensively with these systems to achieve desired creative and artistic implications. Understanding the impact of datasets on the aesthetics and biases of generative artificial intelligence, and how dataset design influences creative output, is also crucial for optimizing prompts and troubleshooting unexpected results. The course's focus on generative systems and their practical application is central to becoming an effective Prompt Engineer.
Academic Researcher Digital Humanities
As an Academic Researcher Digital Humanities, you investigate the complex interplay between technology, culture, and human society. This course is an excellent foundation for such studies, offering critical insight into how artificial intelligence transforms the way we create, interpret, and engage with images and visual media. You will explore generative tools, datasets, and their cultural impact, preparing you to contribute to scholarly discourse. The course's examination of ethical, legal, and political questions surrounding artificial intelligence image-making, along with parallels drawn between artificial intelligence and the history of photography, provides a rich framework for research. Discussions on social debates surrounding artificial intelligence art platforms and dataset ethics are particularly relevant for identifying key areas of inquiry in this rapidly evolving field. An advanced degree is typically required for this profession.
Digital Curator
A Digital Curator specializes in selecting, interpreting, and presenting digital and artificial intelligence generated art to the public. This course is an excellent fit, providing both the critical insight and technical understanding necessary to engage deeply with this evolving art form. You will learn how artificial intelligence systems generate images and how artists use them creatively, allowing you to contextualize contemporary artificial intelligence art within broader art historical narratives, particularly in parallel with photography. The course's strong emphasis on evaluating the ethical and legal implications of artificial intelligence image-making, including issues of consent, appropriation, and authorship, is fundamental for making informed curatorial decisions and fostering meaningful discussions around artificial intelligence art platforms. This critical reflection is vital for a Digital Curator shaping the understanding of this new creative frontier.
Intellectual Property Lawyer Artificial Intelligence Focus
As an Intellectual Property Lawyer Artificial Intelligence Focus, you navigate complex legal questions surrounding innovation and creative works. This course may be very useful by providing a critical understanding of the ethical and legal implications of artificial intelligence image-making, including issues of consent, appropriation, and authorship. You will gain insight into the political and legal issues that arise from the creation of image datasets for artificial intelligence, and discuss the legal challenges facing large artificial intelligence art platforms. These discussions are directly relevant to contemporary debates in intellectual property law regarding ownership and originality in artificial intelligence generated content. While a law degree is essential, this course offers crucial contextual knowledge for specializing in this cutting-edge area of practice.
Visual Effects Artist
As a Visual Effects Artist, you contribute to creating stunning cinematic and media experiences. This course may be very useful by introducing you to how artificial intelligence is transforming visual media production. You will explore how artificial intelligence can be used to generate and manipulate images through techniques like diffusion models, which are increasingly relevant for creating backgrounds, textures, or even character elements. The practical opportunities to experiment with text-to-image tools and other generative systems can directly inform rapid prototyping and ideation workflows. Understanding how artists are engaging with artificial intelligence in practice helps Visual Effects Artists integrate these powerful new tools into their existing skill sets, expanding creative possibilities within film, television, and game development.
Concept Artist
A Concept Artist develops visual ideas for characters, environments, and objects for industries such as gaming and film. This course may be very useful by providing hands-on experience with generative artificial intelligence tools that can significantly accelerate and diversify the ideation process for a Concept Artist. You will experiment with text-to-image tools and other generative systems, gaining insight into how artists are working with artificial intelligence in practice to rapidly explore different visual styles and themes. Understanding how artificial intelligence can be used to generate and manipulate images provides a powerful skill for iterating on concepts quickly. The course also encourages a critical perspective on how generative systems work and relate to earlier image-making technologies, enriching your approach to visual development.
Game Artist
As a Game Artist, you bring virtual worlds to life through visual design, creating assets, environments, and character designs. This course may be very useful by introducing you to how generative artificial intelligence can enhance and revolutionize game art workflows. You will experiment with text-to-image tools and other generative systems, gaining insight into how artists are working with artificial intelligence in practice, which can directly inform rapid prototyping, concepting, and asset generation for games. Understanding how artificial intelligence can be used to generate and manipulate images, using techniques like diffusion models, provides a powerful toolset for creating unique and diverse visual elements. The course offers technical understanding and critical insight to begin experimenting with artificial intelligence in your own creative media practice, a valuable skill for an innovative Game Artist.
Design Researcher
As a Design Researcher, you explore new methodologies, technologies, and user needs to inform design innovation. This course may be useful by offering valuable insights into how artificial intelligence is transforming visual culture and media, providing new lenses for design inquiry. You will explore how artificial intelligence generates images, understanding the influence of datasets on aesthetics and biases, which is critical for evaluating future design tools and their societal impact. The course's examination of ethical, legal, and political questions arising from artificial intelligence image-making helps a Design Researcher identify potential challenges and opportunities in artificial intelligence-driven design processes. This blend of practical understanding of generative systems and critical reflection on their implications helps inform forward-thinking design strategies.
Digital Marketing Strategist
A Digital Marketing Strategist develops and implements marketing campaigns across digital channels. This course may be useful by providing practical insights into how artificial intelligence can be used to generate and manipulate images, offering new avenues for creating compelling visual content for campaigns. Experimenting with text-to-image tools allows a Digital Marketing Strategist to rapidly prototype and produce diverse visual assets, enhancing engagement and brand messaging. Understanding the impact of datasets on the aesthetics and biases of generative artificial intelligence is also important for ensuring brand consistency and avoiding unintended cultural missteps. The course helps build capabilities for leveraging emerging artificial intelligence technologies to elevate digital marketing efforts.
Content Creator Digital Media
As a Content Creator Digital Media, you produce engaging visual and multimedia content for various online platforms. This course may be useful by introducing you to how artificial intelligence is transforming content creation workflows. Through hands-on activities, you will experiment with text-to-image tools and other generative systems, gaining practical skills in generating and manipulating images. Understanding how artists are working with artificial intelligence in practice provides valuable insights for developing innovative and distinctive content. The course's focus on generative systems offers a powerful toolkit for rapidly producing diverse visual assets, enhancing your ability to captivate audiences and stand out in the competitive digital media landscape.
User Experience Designer
As a User Experience Designer, you focus on creating intuitive and satisfying interactions with digital products. This course may be useful by introducing you to the capabilities of generative artificial intelligence in visual media, which can inform the design of future user interfaces and interactive experiences. You will experiment with text-to-image tools and other generative systems, which may assist in rapid prototyping of visual elements or exploring diverse design options for user interfaces. Understanding the cultural impact and ethical implications of artificial intelligence image-making, including issues of bias in datasets, is also important for designing responsible and inclusive artificial intelligence-powered user experiences. This course helps broaden a User Experience Designer's understanding of emerging visual technologies.

Reading list

We've selected 50 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Creative AI: Images and Media .
The definitive benchmark textbook of modern artificial intelligence, rigorously unifying search algorithms, probabilistic reasoning, knowledge representation, and machine learning into an elegant, coherent agent-based framework.
A monumental foundational text establishing the mathematical, algorithmic, and statistical principles of modern deep neural networks, from linear algebra and optimization to convolutional and sequence modeling architectures.
This essential reader provides a comprehensive overview of the field of media studies, covering key theoretical approaches, historical developments, and contemporary debates.
Provides an exceptionally practical, code-first curriculum that guides engineers from end-to-end data preprocessing and traditional regression pipelines to production deep learning models and generative neural networks.
The second edition of Foster's book, updated to include recent advancements like diffusion models, making it highly relevant to contemporary image generation. It offers a practical guide to building generative models with TensorFlow and Keras. This edition is particularly valuable for understanding the latest techniques.
Delivers an authoritative mathematical foundation in Bayesian inference, graphical models, and statistical learning algorithms, bridging foundational probability theory with rigorous predictive computational modeling.
Comprehensive guide to the challenges and solutions in designing systems that handle large amounts of data. It covers various data storage and processing technologies and the trade-offs involved. It's highly relevant for data engineers and software architects working with complex data systems, offering in-depth knowledge on contemporary data architecture patterns.
Guides engineers step-by-step through implementing, training, and fine-tuning complete generative transformer architectures in pure PyTorch, providing crystal-clear low-level insight into modern foundation models.
This recent book focuses on two of the most impactful contemporary architectures in generative AI: Transformers and Diffusion Models, both crucial for state-of-the-art image generation. It provides hands-on experience, making it highly relevant for those looking to implement modern techniques.
Presents the foundational treatise on Markov decision processes, temporal-difference learning, and policy gradient methods that underpin autonomous decision-making and modern post-training alignment workflows.
Examines holistic architectural patterns for designing resilient machine learning infrastructure, addressing data pipelines, real-time feature stores, continual learning loops, and production deployment reliability.
This widely recognized and comprehensive textbook covering the fundamental concepts of database systems. It provides a deep understanding of database design, languages (including SQL), and implementation techniques. It's a cornerstone resource for undergraduate and graduate students in computer science and a solid reference for professionals.
This handbook provides a comprehensive overview of the intersection of media, technology, and society, covering topics such as digital media, social media, and the impact of technology on media industries.
Given the mention of Spark in the course titles, this book direct and highly relevant resource for understanding and utilizing Apache Spark for big data processing. Written by one of Spark's creators, it provides in-depth coverage of the Spark architecture and its various APIs. It's a must-read for anyone working with Spark.
Demystifies practical transformer model implementation through the Hugging Face ecosystem, demonstrating how to fine-tune, optimize, and deploy attention architectures across diverse natural language processing and understanding tasks.
A comprehensive history of Western art from ancient times to the present day. It provides a detailed overview of the major movements, artists, and works of art that have shaped the development of visual arts in the West.
Provides a practical guide to using generative AI, covering the different techniques and tools available. It is written by two leading experts in the field, Josh Patterson and Adam Gibson.
A comprehensive overview of the history of art from ancient times to the present day. It provides a broad understanding of the major movements, artists, and works of art that have shaped the development of visual arts.
Offers a hands-on approach to understanding and implementing GANs. It covers the fundamental architecture of GANs and guides readers through building and training their own models. This practical guide suitable for those with intermediate Python and basic deep learning skills who want to gain practical experience with GANs.
Data cleaning crucial step in any data-related project. provides a practical guide to identifying and handling errors and inconsistencies in datasets. It's a valuable resource for anyone involved in preparing data for analysis or modeling, offering techniques and strategies for ensuring data quality.
Delves into more contemporary aspects of data engineering using Spark in conjunction with Delta Lake and the Lakehouse concept. It's relevant for those looking to build modern data architectures that combine the benefits of data lakes and data warehouses. This book is suitable for professionals seeking to deepen their understanding of current big data technologies.
Delivers battle-tested operational patterns for serving foundation models, addressing GPU cluster throughput, semantic caching, automated evaluation benchmarks, and continuous latency minimization.
Offers a highly accessible and intuitive introduction to the core concepts of statistics. It demystifies statistical principles without relying heavily on complex mathematics, making it ideal for those new to the subject or looking to build a strong conceptual foundation. It serves as excellent background reading for understanding the statistical basis of data analysis.
Details an applied architectural methodology for running high-performance open-weights models on local workstations, tackling quantization fidelity, memory bandwidth limits, and prompt assembly trade-offs.
Focuses on the business applications of data science and how to approach business problems with a data-analytic mindset. It covers data mining techniques and the process of extracting valuable insights from data. It's particularly relevant for those interested in applying dataset analysis to solve business challenges and is often used as a textbook in business analytics programs.
Offers an accessible yet rigorous introduction to deep learning, including a chapter dedicated to diffusion models. It strikes a balance between theory and practice, providing intuitive explanations and covering important models. It is suitable for students and researchers looking for a solid understanding of deep learning concepts, including the fundamentals of diffusion models.
Offers a rigorous theoretical foundation for reasoning under uncertainty, combining graph theory and probability distributions to model complex high-dimensional dependencies across autonomous intelligent systems.
Provides a practitioner-focused view of generative AI, including image generation, with an emphasis on real-world applications, deployment, and ethical considerations. It's valuable for professionals looking to integrate generative AI into their work.
A comprehensive guide to the use of color and light in painting, covering topics such as color theory, values, and composition.
Is an essential read for anyone working with data, regardless of their technical background. It provides a foundational understanding of how statistics can be misused and misinterpreted, which is crucial for developing data literacy and critically evaluating information presented with data. It short and accessible book, making it excellent for beginners and a valuable quick reference for anyone.
Introduces core computational linguistics concepts and practical tokenization, tagging, and syntactic parsing workflows through clear Python examples, establishing strong fundamentals for language analysis.
Examines the relationship between media and power, covering topics such as media ownership, media bias, and the role of media in political campaigns.
While not solely focused on diffusion models, this widely-used textbook on deep learning includes updated content on generative AI, including diffusion models, in its third edition. It is an excellent resource for building a strong foundation in deep learning concepts and practical implementation using Keras and TensorFlow, which are essential prerequisites for understanding and working with diffusion models.
Provides a comprehensive survey of Text-to-Image generation models, covering different approaches, techniques, and evaluation methods.
This comprehensive online book on deep learning that includes coverage of GANs. It's an excellent resource for building a strong foundation in deep learning, which is essential for understanding GANs in depth. It's freely available and widely used in courses.
Building on the ethical considerations, this book offers a critical lens on data science through the framework of intersectional feminism. It explores how power dynamics and biases are embedded in datasets and data-driven systems and proposes ways to work towards data justice. is particularly relevant for understanding contemporary social issues related to data.
Synthesizes the five foundational tribes of machine learning into a unified conceptual framework, illuminating how symbolists, connectionists, evolutionaries, Bayesians, and analogizers approach intelligence.
Provides a comprehensive overview of various deep generative models, with a dedicated chapter on GANs. It covers the theoretical foundations and includes code snippets. It's a valuable resource for understanding the broader landscape of generative AI beyond just GANs and is suitable for readers with a modest mathematical background.
Offers a practical, step-by-step guide to using Midjourney, a popular AI image generation tool. While less focused on the underlying models, it's highly relevant for users looking to create images with AI and understand prompting techniques. It's a valuable resource for practical application.
Connecting to the TensorFlow course mentioned, this book focuses on operationalizing machine learning models by building robust pipelines. It addresses the practical aspects of taking models from experimentation to production, which often involves managing and processing datasets. is valuable for those interested in the practical application of data in machine learning workflows.
Focuses on practical implementation of GANs using the Keras library. It offers step-by-step instructions and projects, making it valuable for those who want to get hands-on experience building GANs. It's a good resource for solidifying understanding through practical application.
Focuses on the application of Text-to-Image in the arts and design industry, providing practical guidance on using the technology to create stunning visuals.

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