Unleash your Creativity with Stable Diffusion AI

Name: Unleash your Creativity with Stable Diffusion AI
Rating: 3.9 (258 reviews)
Author: Techlatest.net

Stable Diffusion

updated on icon Updated on Apr, 2024

language icon Language - English

English [CC]

Lectures -13

Duration -1.5 hours

3.9 ★★★ ★ ★

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Course Description

This course will teach you how to use the powerful Stable Diffusion AI image generator to unleash your creativity and supercharge your productivity as an artist, designer, creative professional & app developer.

You'll learn how to generate stunning digital art from simple text prompts and customize the model to align with your creative vision. The course covers the techniques behind text-to-image synthesis like diffusion models, latent spaces, and attention mechanisms.
Deployment & setup of Stable Diffusion on AWS, GCP & Azure Cloud platforms.
Through hands-on exercises, you'll gain practical skills for harnessing Stable Diffusion to generate concept art, illustrations, variations, and novel ideas that can transform your work.
The course also covers best practices for prompt engineering to exploit the different features of Stable Diffusion.
The course also covers topics like API(Application Programming Interface) for App developers to create custom apps using Stable Diffusion.
How to further customize your generated images by using ControlNet, Dreambooth & Custom models.
Learn how to extend Stable Diffusion & Automatic1111 Functionality using plugins.
By the end of the course, you will be able to use Stable Diffusion as a creative tool that amplifies your imagination and helps you produce more compelling images, graphics, and visual content for your projects.

What will you learn in this course:

Artists and creative professionals interested in learning how to use AI image-generation tools in their work. Stable diffusion can help generate novel concepts, variations, and ideas.
Developers and machine learning engineers want to learn how to build and customize stable diffusion models. The course would cover the underlying architecture and techniques.
Researchers studying generative models, text-to-image synthesis, and diffusion models. The course content could provide insights and inspiration for new research directions.
Students in computer science, machine learning, or artificial intelligence programs. A stable diffusion course could help teach important concepts like generative modelling, latent spaces, and diffusion processes through a practical application.
Anyone curious about the capabilities of modern generative AI and wanting to learn how to harness this technology in an ethical and responsible manner. The course would likely cover best practices, limitations, and societal considerations.

What are the prerequisites for this course?

Basic computer vision knowledge. Concepts like images, pixels, channels, kernels, and filters. This will help us understand how Stable Diffusion works.
Curiosity and interest in generative AI and text-to-image models. A desire to learn how to use these powerful new tools to create novel images.

Check out the detailed breakdown of what’s inside the course

Introduction
13 Lectures

01-Course+Introduction+of+Learn+Stable+Diffusion+using+Automatic1111+web+interface 06:12 06:12
02 Introduction to Generative AI & Stable Diffusion 07:22 07:22
03 Setup of Stable Diffusion with Automatic1111 web interface on AWS 11:24 11:24
04 Setup of Stable Diffusion with Automatic1111 web interface on GCP 10:11 10:11
05 Setup of Stable Diffusion with Automatic1111 web interface on Azure 11:53 11:53
06-01- Introduction to Automatic1111 features Part 1 11:09 11:09
06-02- Introduction to Automatic1111 features Part 2 11:35 11:35
06-03- Introduction to Automatic1111 features Part 3 07:13 07:13
07 Enabling Stable Diffusion API and How to run it A Step-by-Step Guide 07:40 07:40
08 Introduction to ControlNet A Step-by-Step Guide 08:11 08:11
09 Introduction to Dreambooth A Step-by-Step Guide 07:02 07:02
10 Intro to Automatic1111 & Stable Diffusion functionality using Extensions 05:58 05:58
11 Introduction to Stable Diffusion models in Automatic1111 09:31 09:31