This deep learning course provides a comprehensive introduction to AI image generation using Stable Diffusion, denoising techniques, and advanced generative learning methods. Begin by understanding how Stable Diffusion models generate high-quality visuals from text prompts through latent representations. Learn denoising methods that improve image quality during training and inference. Gain hands-on experience with a live demo on text-to-image generation. Progress to generative learning using autoencoders and contrastive learning to enhance feature representation. Explore shared embedding spaces and how to align images, text, and code for cross-modal GenAI applications.
Image Generation with AI Training Course
Gain insight into a topic and learn the fundamentals.
Beginner level
Recommended experience
3 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
Generate high-quality images using Stable Diffusion models
Apply denoising techniques to refine generative outputs
Use autoencoders and contrastive learning for feature enhancement
Build shared embedding spaces for multimodal AI applications
Skills you'll gain
Details to know
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Recently updated!
June 2025
Assessments
6 assignments
Taught in English
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There are 2 modules in this course
Master AI image generation with Stable Diffusion and denoising techniques in this hands-on module. Learn how Stable Diffusion models generate high-quality visuals from text prompts using latent representations. Explore denoising methods that refine image outputs during training and inference. Gain practical experience with a live demo on text-to-image generation using Stable Diffusion.
What's included
4 videos1 reading3 assignments
Explore advanced generative learning techniques and embedding spaces in this module. Learn how autoencoders and contrastive learning enhance generative AI models by improving feature representations. Understand shared embedding spaces and how to embed images, text, and code for cross-modal AI tasks. Ideal for building powerful, multimodal GenAI applications.
What's included
5 videos3 assignments
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Frequently asked questions
AI image generators are typically trained on large datasets of images and captions using models like GANs or diffusion models. These models learn to map patterns between text and visual features to generate realistic images.
Stable Diffusion, DALL·E 2, and Midjourney are among the best AI tools for image generation, offering high-quality, customizable results across various styles and use cases.
Certifications that cover Stable Diffusion, GANs, and embedding spaces like those offered by Simplilearn, DeepLearning.AI, or Coursera; are ideal for mastering AI-based image generation.
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