Aspire Journeys
Image Generation with AI
- 7 Courses | 9h 21m 42s
The Image Generation with AI journey is designed to take learners through the transformative world of AI-powered image creation, blending creativity with cutting-edge technology. Across six in-depth courses, participants will explore foundational concepts such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) and progress to advanced frameworks like Stable Diffusion, all within hands-on environments like Keras. The journey begins by laying the groundwork with the history and significance of AI in image generation, followed by comprehensive dives into the core frameworks and their real-world applications. Learners will not only develop a strong understanding of the mathematical and technical foundations but will also gain practical experience through demonstrations, fine-tuning techniques, and projects that challenge their creativity. By the end of this journey, participants will be equipped with the skills and knowledge to generate high-resolution, AI-driven visual content, positioning themselves at the forefront of AI and visual arts innovation.
Track1: Mastering Image Generation with AI
This track begins with the history and significance of AI in image generation, followed by comprehensive dives into the core frameworks and their real-world applications. Learners will not only develop a strong understanding of the mathematical and technical foundations but will also gain practical experience through demonstrations, fine-tuning techniques, and projects that challenge their creativity.
- 7 Courses | 9h 21m 42s
COURSES INCLUDED
Introduction to AI-powered Image Generation
Artificial intelligence (AI) has taken the world by storm, and image generation has become one of AI's most interesting contributions to the modern world. In this course, examine the pros and cons of generative AI (GenAI), the history of image generation, the uses of AI in creative content generation, and generative AI models and methods. Next, discover how to use generative AI to create content, generative AI pipeline components, and use cases for generative AI. Finally, learn about popular generative AI frameworks and tools, ethical considerations of generative AI, how AI influences art, the implications of generative AI, and the possible future of generative AI. After course completion, you'll be able to comprehensively describe the fundamentals of AI-powered image generation.
16 videos |
2h 5m
Assessment
Badge
Image Generation Frameworks
Amazing, controversial, and game-changing. It's remarkable to think that we're only at the beginning, only starting to see the opportunities offered by artificial intelligence (AI)-powered image generation. Yet here we are, at the start of a technological marvel that's taking the world by storm. In this course, you'll explore image generation frameworks, beginning with variational autoencoders (VAEs), generative adversarial networks (GANs), and comparing GANs and VAEs. Then you'll explore GAN architectures, GAN use cases, GAN training, and the DCGAN, WGAN, CycleGAN, and StyleGAN architectures. Finally, you'll learn about autoregressive models, autoregressive models in comparison to other techniques, diffusion models, diffusion model use cases, and the pros and cons of image generation frameworks.
17 videos |
1h
Assessment
Badge
Mathematical Foundations of Image Generation
Artificial intelligence has taken the world by storm over the past few years, and it is remarkable to think that we are only starting to see the opportunities offered by AI-powered image generation. To grasp the inner workings of the technology, an understanding of the mathematical foundations of AI-powered image generation is critical. In this course, you will explore the mathematical foundations of image generation, beginning with the role of generative adversarial networks (GANs) in image generation, basic GAN usage, probability distributions, and generative models. Then you will learn about noise vectors, activation functions in GANs, and loss functions. Next, you will investigate backpropagation, conditional GANs, and style transfer methods. You will discover latent space and adversarial training. Finally, you will create your own GAN-based image generation project.
15 videos |
1h 36m
Assessment
Badge
Mastering Image Editing with VAEs
With artificial intelligence (AI)-powered image generation, you are only limited by your imagination, your understanding of the technology, and the AI's capabilities in what you can accomplish. With a good understanding of generative AI, the sky's the limit. In this course, you'll be introduced to image editing with variational autoencoders (VAEs), beginning with fundamental principles of VAEs, probabilistic encoding and decoding with VAEs, and latent space in generative models. Then you'll be introduced to Keras, the Keras Environment, image editing with VAEs, and VAE training. Finally, you'll explore latent space variables in Keras, how to build an autoencoder in Keras, how to generate images with Keras, and Keras case studies.
13 videos |
1h 31m
Assessment
Badge
Image Generation with Stable Diffusion in Keras
Multiple technologies and techniques are used in artificial intelligence (AI)-powered image generation, and this broad field is growing so much every day that you would be forgiven for feeling overwhelmed by the opportunities. In many ways, AI image generation is in the very early stages, so it is staggering to think about what the future holds. In this course, you will be introduced to image generation with Stable Diffusion in Keras, beginning with an overview of Stable Diffusion and diffusion models. Then you will examine variations of diffusion models and uses for diffusion models. You will explore high-resolution image creation, realism, and detail enhancement with Stable Diffusion. Next, you will learn how to implement Stable Diffusion with Keras. Finally, you will investigate methods for prompt creation, inpainting, latent diffusion, and Stable Diffusion models.
13 videos |
1h 14m
Assessment
Badge
High-resolution Image Generation
Image generation is one of the most interesting contributions artificial intelligence (AI) is making to the modern world, and we have only scratched the surface of what is possible. Because AI image generation is still in its early stages, we have to wonder what the future holds. In this course, you will be introduced to high-resolution image generation with AI, beginning with Stable Diffusion use cases, model construction, and model training. Then you will delve into fine-tuning strategies, denoising diffusion models with Keras, and high-resolution image generation in Keras. Next, you will explore the advantages of high-resolution image generation in Keras, the inner workings of image generation, and the impact that Stable Diffusion has on AI-powered image generation. Finally, you will investigate the steps involved in moving an image generator to a cloud provider.
11 videos |
59m
Assessment
Badge
Final Exam: Image Generation with AI
Final Exam: Image Generation with AI will test your knowledge and application of the topics presented throughout the Image Generation with AI journey.
1 video |
32s
Assessment
Badge
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