Image Generation with AI E-Learning

Ontdek hoe kunstmatige intelligentie de wereld van beeldgeneratie transformeert met onze Image Generation with AI Training. Leer de nieuwste AI-technieken voor het creëren van verbluffende beelden. Boek nu en stap in de toekomst van visuele content!

This LearningKit with more than 8 hours of learning is divided into three tracks:

Demo Image Generation with AI Training

Course content

Introduction to AI-powered Image Generation

Course: 2 Hours, 5 Minutes

• Course Overview
• AI Image Generation
• The Pros and Cons of Generative AI
• The History of Image Generation
• AI in Creative Content Generation
• Popular Generative AI Models
• Generative AI Methods
• How Generative AI Is Used to Create Content
• Components of a Generative AI Pipeline
• Use Cases for Generative AI
• Popular Generative AI Frameworks and Tools
• Ethical Considerations of Generative AI
• How AI Influences Art
• The Implications of Generative AI
• The Future of Generative AI
• Course Summary

Image Generation with AI: Image Generation Frameworks

Course: 1 Hour, 55 Minutes

• Course Overview
• Variational Autoencoders (VAEs)
• Generative Adversarial Networks (GANs)
• Comparing GANs and VAEs
• Introduction to GAN Architectures
• GAN Use Cases
• GAN Training
• Implementing the DCGAN Architecture
• Implementing the WGAN Architecture
• Implementing the CycleGAN Architecture
• Implementing the StyleGAN Architecture
• Autoregressive Models
• Comparing Autoregressive Models to Other Techniques
• Diffusion Models
• Diffusion Model Use Cases
• Pros and Cons of Image Generation Frameworks
• Course Summary

Mathematical Foundations of Image Generation

Course: 1 Hour, 36 Minutes

• Course Overview
• Generative Adversarial Networks (GANs) in Image Generation
• Exploring Basic GAN Usage
• Probability Distributions
• Comparing Generative Models
• Noise Vectors
• Using Activation Functions in GANs
• Loss Functions
• Backpropagation
• Conditional GANs
• Style Transfer Methods
• Latent Space
• Adversarial Training
• Creating a GAN Project
• Course Summary

Image Generation with AI: Mastering Image Editing with VAEs

Course: 1 Hour, 31 Minutes

• Course Overview
• Principles of Variational Autoencoders (VAEs)
• Probabilistic Encoding and Decoding with VAEs
• Latent Space in Generative Models
• Introduction to Keras
• Navigating the Keras Environment
• Image Editing with VAEs
• Training VAEs
• Latent Space Variables in Keras
• Building an Autoencoder in Keras
• Generating Images with Keras
• Keras Case Studies
• Course Summary

Image Generation with AI: Image Generation with Stable Diffusion in Keras

Course: 1 Hour, 14 Minutes

• Course Overview
• Stable Diffusion
• Diffusion Models
• Variations of Diffusion Models
• Uses for Diffusion Models
• How Stable Diffusion Unleashes High-resolution Image Creation
• Enhancing Realism and Detail with Stable Diffusion
• Implementing Stable Diffusion with Keras
• Methods for Prompt Creation
• Inpainting
• Latent Diffusion
• Stable Diffusion Models
• Course Summary

Image Generation with AI: High-resolution Image Generation

Course: 59 Minutes

• Course Overview
• Stable Diffusion Use Cases
• Constructing and Training a Model
• Fine-tuning Strategies
• Denoising Diffusion Models with Keras
• High Resolution Image Generation in Keras
• Advantages of High-resolution Image Generation in Keras
• Generating Images
• The Impact of Stable Diffusion
• Moving to a Cloud Provider
• Course Summary

Assessment:

• Final Exam: Image Generation with AI