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Master AI Art: Stable Diffusion, Automatic1111
Rating: 4.4 out of 5(190 ratings)
27,670 students

Master AI Art: Stable Diffusion, Automatic1111

Generate Stunning AI Images & Videos with Prompt Engineering, Automatic1111 and More. For Artists & Architects
Last updated 6/2026
English

What you'll learn

  • learning about diffusion models
  • practical applications of AI-generated images
  • students will have the knowledge and skills to build their own machine that can generate realistic images
  • How to generate your own art using AI
  • learning about diffusers package
  • learning about Automatic1111 and how to use it
  • How to understand and implement research papers
  • How to build a system to convert your video into animation
  • How to use diffusers library
  • How to convert your audio to video using AI

Course content

12 sections100 lectures21h 17m total length
  • What you will learn in this course ?2:28
  • what is stable diffusion ?11:29
  • Where to find the codes ?2:24
  • How does stable diffusion model work?1:19
  • what is gaussian distribution?7:39
  • What is Markove chain ?4:12
  • What is Forward diffusion ?7:32
  • What is Reparameterization Trick ?11:44
  • What is variance schedule ?6:37
  • Linear variance schedule Vs cosine-based variance schedule4:23
  • What is Reverse diffusion ?10:21
  • How can we train our network part1 ?3:19
  • How can we train our network part2 ?10:54
  • How can we train our network part3 ?1:56
  • How can we train our network part4 ?2:54
  • Stable Diffusion Inference4:04
  • What is U network ?9:47
  • How to create Unconditional diffusion model ?4:49
  • What is positional embedding ?10:58
  • How to create Conditional diffusion model ?9:18

Requirements

  • Basic understanding of machine learning concepts
  • Programming skills

Description

Welcome to this in-depth and comprehensive course where you will explore the fascinating world of artificial intelligence and learn how to generate realistic images using cutting-edge techniques. With the rapid development of deep learning and neural networks, the potential of AI-generated images is enormous. In this course, you will learn how to build your own machine that can generate images that look strikingly real.

You will start with an introduction to diffusion models, which are a powerful class of models that can be used for image generation. You will explore how they work, their underlying principles, and how to use them in different tasks like inpainting and image-to-image generation. You will also delve into the techniques that are used to train these models and how they can be optimized to produce the best possible results.

Throughout the course, you will gain hands-on experience with practical applications of AI-generated images. You will learn how to use diffusion models to create stunning, high-quality images for a variety of applications. You will also gain an understanding of the ethical implications of AI-generated images and how to navigate these issues in your work.

By the end of the course, you will have the knowledge and skills to build your own machine that can generate realistic images using AI. You will have a deep understanding of the underlying principles of diffusion models and how to apply them to create images that are not only realistic but also aesthetically pleasing. Whether you are a beginner or an experienced AI developer, this course will equip you with the tools you need to take your work to the next level.


Who this course is for:

  • students
  • professionals