We may earn an affiliate commission when you visit our partners.
Course image
Pixovert Studio

This course is a complete introduction to the nearly magical art of designing images by the use of generative AI.

Read more

This course is a complete introduction to the nearly magical art of designing images by the use of generative AI.

Stable diffusion is one of the most powerful AI tools released by Stability AI and it provides a thorough basis for learning about generative AI generally, but also it can be used, with sufficient skill, in a production environment.

The course includes the following

•An Introduction to Stable Diffusion

•A guide to Installing Stable Diffusion using an Nvidia Graphics Card

•Understand the user interface

•Understanding Key Features

Key concepts learned include prompt construction, evalution and optimization.

Stable Diffusion is a latent diffusion model, a kind of deep generative neural network. Its code and model weights have been released publicly, and it can run on most consumer hardware equipped with a modest GPU with at least

The course explores options for users with less powerful equipment.

Stable Diffusion is entirely free and open-source, with no restrictions on commercial use. It is the most flexible AI image generator that you can even train your own models based on your own dataset to get it to generate exactly the kind of images you want

Students also learn where to get valuable resources like 3rd party checkpoints and models which can be used to improve the workflow and to provide creative freedom.

Stable Diffusion is a deep learning, text-to-image model that is primarily used to generate detailed images conditioned on text descriptions. It can also be applied to other tasks such as inpainting, outpainting, and generating image-to-image translations guided by a text prompt1. The main use cases of stable diffusion include:

Text-to-Image: the classic application where you enter a text prompt and Stable Diffusion generates a corresponding image.

Image-to-Image: tweak an existing image. You provide an image and a prompt and SD uses your image and tweaks it towards the prompt.

Inpainting: tweak an existing image only at specific masked parts.

Outpainting: add to an existing image at the border of it.

Enroll now

What's inside

Learning objectives

  • Understand the evolution of stable diffusion from concept to image-creation powerhouse
  • Learn to install the automatic1111 version of stable diffusion with step-by-step instructions
  • Find your way around the webui user interface
  • Gain a thorough beginner's understanding of artificial intelligence prompt construction

Syllabus

Course Introduction and Objectives

Understand course structure and content and core course aims.

What you need to complete the course.

The version of Stable Diffusion used in this course requires a discrete graphics processor.

To follow along with installation steps an Nvidia graphics card with at least 8GB of VRAM is required.  I would recommend an entry level RTX 30 series Nvidia graphics card, the newer RTX 40 series Nvidia graphics cards, however earlier editions with 8GB of VRAM will also provide optimal performance.

Students who already understand how to set up Nvidia low VRAM installations or AMD installations of AUTOMATIC1111 can skip this part.

Towards the end of the course are some advices on how to set up and run on a low VRAM system.

Read more

This is the core learning for anyone starting Stable Diffusion. 

  • By the end you will understand the origins of Stable Diffusion, the capabilites of this artificial intelligence

  • The strengths and weaknesses of the Latent Diffusion model

  • The advantages of AUTOMATIC1111

Learn to Install an AUTOMATIC1111 instance of Stable Diffusion

Students will learn how to install AUTOMATIC1111 and Xformers

  • Learners will be able to install an AUTOMATIC1111 instance of Stable Diffusion in a PC with an Nvidia GPU with 8GB or more of VRAM

  • Learners will be able to install the important Xformers Accelerator from Meta Research

The Dreamshaper model which is only a 2GB download may be used instead of the Runway checkpoint.

This is a very recent update showing a new way of Installing Automatic1111's WebUI in a standalone version which increases compatibility with other user interfaces for Stable Diffusion - for instance ComfyUI.

This is optional, the course can be completed without it, but learners may prefer to test out both installations to see which suits requirements best.

Be able to navigate the Stable Diffusion User interface

Core ideas to understand the functioning of Stable Diffusion including a preliminary look at prompts.

This lecture provides a deep understanding of the interplay between different parts of the user interface.  This is introductory, but covers most of the aspects we shall utilize in this course.

Understand the role samplers / sampling methods in image generation.  Samplers are a core parameter in operating stable diffusion.

Understanding the 'Maths' section in Stable Diffusion.  Don't worry this is not a math lecture.

How to analyse, assess and optimize output, and a very brief outline of some of the advanced features in Stable Diffusion

A deep dive into some more advance methods and criteria in prompt construction. 

Students will learn how to use English language instructions and prompt commands to produce optimal and reliable image outputs.

Learn which hardware upgrades are most effective in removing bottlenecks in your workflows
How to choose the best Hardware to Improve Performance
Learn advanced techniques for working with Stable Diffusion and plugins

The benefits of using custom models are profound.  This video examines how to access checkpoint and textual inversion models and how to use them with Stable Diffusion.

ControlNets

Automatic1111 can be used to install Controlnets, IPAdapters and T2I adapters.

This is a sketch outline on how these can be installed and deployed within Automatic 1111.  This requires at a minimum version 1.6 of Automatic1111.

Understand the power, utility and versatility of the latent diffusion model using practical techniques

Generative Fill is a term used by Adobe to describe the process of using generative AI to remove or replace an object in Photoshop.  This is possible in stable diffusion and we look at the process in this lecture.

Comparison of methods for optimizing installations for low VRAM GPUs

Automatic1111 provides several options for working with Graphics Cards with less than 8GB of Memory.  There may be times when you would want to use optimizations like this even when you have 8GB of VRAM as it may nonetheless prove a bottleneck with more complex workflows..  What are these methods and how well do they work? 

Learn how to manually update your installation of Stable Diffusion.

This video demonstrates a technique for upgrading the installation Automatic1111 of Xformers.   This isn't an essential technique.  Some students have reported issues after upgrades, so you may want to skip this until you are more sure of your abilities to fix any issues you may encounter in your installation.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Examines Stable Diffusion, the fundamentals of generative AI, and its use cases in a production environment. This course is a comprehensive overview of the tool and its possibilities
Teaches students how to install and configure Stable Diffusion using an Nvidia Graphics Card, ensuring a smooth setup process
Develops a comprehensive understanding of Stable Diffusion's user interface, empowering learners to confidently navigate the platform
Explores prompt construction, evaluation, and optimization, which are crucial skills for effectively using Stable Diffusion
Provides practical guidance on working with Stable Diffusion and plugins, enhancing learners' workflow and efficiency
Teaches advanced techniques for optimizing installations for low VRAM GPUs, enabling learners to utilize their hardware resources effectively

Save this course

Save Beginner's Guide to Stable Diffusion with Automatic1111 to your list so you can find it easily later:
Save

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Beginner's Guide to Stable Diffusion with Automatic1111 with these activities:
Review Latent Diffusion Models
Strengthen your understanding of the underlying principles of Stable Diffusion by revisiting the concepts of latent diffusion models.
Browse courses on Machine Learning
Show steps
  • Read articles and watch videos explaining latent diffusion models.
  • Review the course materials on the basics of Stable Diffusion.
  • Participate in online discussions or forums to clarify your understanding.
Practice Prompt Engineering
Enhance your proficiency in crafting effective prompts by regularly practicing writing and optimizing prompts for Stable Diffusion.
Browse courses on Prompt Engineering
Show steps
  • Set aside dedicated time for prompt engineering practice.
  • Gather a variety of image samples to inspire your prompts.
  • Experiment with different combinations of words, phrases, and modifiers to observe the impact on image outputs.
  • Take advantage of online resources and communities to refine your prompt-crafting skills.
Showcase Your Stable Diffusion Creations
Solidify your understanding of Stable Diffusion by applying your skills to create a portfolio of captivating images.
Browse courses on Image Creation
Show steps
  • Brainstorm a theme or concept for your image collection.
  • Craft a series of prompts that effectively convey your desired image outcomes.
  • Experiment with different Stable Diffusion settings and parameters to achieve optimal results.
  • Compile your best images into a portfolio to showcase your skills.
Ten other activities
Expand to see all activities and additional details
Show all 13 activities
Compile a Resource Library
Enhance your learning by gathering and organizing a collection of relevant materials.
Browse courses on Knowledge Management
Show steps
  • Identify and collect valuable resources
  • Categorize and organize the materials
  • Share the resource library with others
Join a Stable Diffusion Study Group
Deepen your comprehension of Stable Diffusion and gain diverse perspectives by engaging in collaborative discussions and knowledge-sharing sessions with other learners.
Show steps
  • Seek out online forums, Discord groups, or local meetups focused on Stable Diffusion.
  • Participate actively in discussions, ask questions, and share your own insights and experiences.
  • Collaborate on projects or challenges to apply your learnings and receive feedback from peers.
Develop a Stable Diffusion Plugin or Extension
Expand your technical skills by creating a plugin or extension that enhances or automates specific tasks within Stable Diffusion.
Browse courses on Software Development
Show steps
  • Identify a specific need or area where you can add value to the Stable Diffusion workflow.
  • Research existing plugins or extensions to understand the landscape and identify opportunities.
  • Develop a plan for your plugin or extension, including its features and functionality.
  • Implement your plugin or extension using the appropriate programming languages and tools.
Facilitate a Study Group
Enhance your understanding by sharing knowledge and engaging in discussions with peers.
Browse courses on Collaboration
Show steps
  • Organize a group of fellow learners
  • Establish a schedule and learning objectives
  • Facilitate discussions and provide feedback
Explore Advanced Stable Diffusion Techniques
Develop mastery in advanced Stable Diffusion techniques to create unique and personalized image results.
Browse courses on Custom Models
Show steps
  • Seek out tutorials and documentation on advanced Stable Diffusion techniques.
  • Practice working with custom models to fine-tune your image generation process.
  • Experiment with image manipulation techniques to enhance and refine your outputs.
  • Explore online communities and forums for tips and tricks.
Contribute to Stable Diffusion Open Source Projects
Enhance your understanding of Stable Diffusion and contribute to its development by participating in open-source projects.
Browse courses on Open Source
Show steps
  • Identify open-source projects related to Stable Diffusion that align with your interests.
  • Review the project documentation and familiarize yourself with the codebase.
  • Identify areas where you can contribute, such as bug fixes, feature enhancements, or documentation improvements.
  • Reach out to the project maintainers to discuss your ideas and seek guidance.
Build a Portfolio of Stable Diffusion Images
Develop your skills and showcase your creativity by crafting a collection of Stable Diffusion images.
Browse courses on Image Generation
Show steps
  • Experiment with different prompts and settings
  • Refine and select your best images
  • Assemble and present your portfolio
Contribute to Stable Diffusion Open Source
Deepen your understanding by contributing to the advancement of Stable Diffusion.
Browse courses on Stable Diffusion
Show steps
  • Identify an area of contribution and submit a pull request
  • Engage in discussions and troubleshoot issues
Explore Custom Stable Diffusion Models
Expand your capabilities by exploring and utilizing custom models for specialized image generation.
Browse courses on Prompt Engineering
Show steps
  • Learn about checkpoint files and training processes
  • Download and experiment with pretrained custom models
  • Fine-tune models using textual inversion or other techniques
Mentor New Stable Diffusion Users
Solidify your understanding and contribute to the community by guiding others in their Stable Diffusion journey.
Browse courses on Mentorship
Show steps
  • Identify opportunities to share your knowledge
  • Provide guidance and support to new users
  • Offer constructive feedback and encouragement

Career center

Learners who complete Beginner's Guide to Stable Diffusion with Automatic1111 will develop knowledge and skills that may be useful to these careers:

Reading list

We haven't picked any books for this reading list yet.

Share

Help others find this course page by sharing it with your friends and followers:

Similar courses

Here are nine courses similar to Beginner's Guide to Stable Diffusion with Automatic1111.
Machine Learning: Modern Computer Vision & Generative AI
Most relevant
Introducing StableDiffusion ComfyUI for...
Most relevant
Your Ultimate Starter Kit on Stable Diffusion
Most relevant
Generative AI Mastery with ComfyUI SDXL and Stable...
Most relevant
Master Generative AI: Automate Content Effortlessly with...
Most relevant
Generative AI: Introduction and Applications
Most relevant
Create Amazing Graphics and Art using Stable Cascade
Most relevant
All of AI: ChatGPT, Midjourney, Stable Diffusion & App Dev
Most relevant
Introduction to Generative AI
Most relevant
Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2024 OpenCourser