Generative AI : Create an impressive AI Art

Course Curriculum

Chapter 1: Introduction

Lecture 1: What you will learn in this course ?

Lecture 2: Where to find the codes ?

Lecture 3: what is stable diffusion ?

Lecture 4: what is gaussian distribution?

Lecture 5: How does stable diffusion model work?

Lecture 6: What is Markove chain ?

Lecture 7: What is Forward diffusion ?

Lecture 8: What is Reparameterization Trick ?

Lecture 9: What is variance schedule ?

Lecture 10: Linear variance schedule Vs cosine-based variance schedule

Lecture 11: What is Reverse diffusion ?

Lecture 12: How can we train our network part1 ?

Lecture 13: How can we train our network part2 ?

Lecture 14: How can we train our network part3 ?

Lecture 15: How can we train our network part4 ?

Lecture 16: Stable Diffusion Inference

Lecture 17: What is U network ?

Lecture 18: How to create Unconditional diffusion model ?

Lecture 19: What is positional embedding ?

Lecture 20: How to create Conditional diffusion model ?

Chapter 2: Unconditional diffusion model

Lecture 1: How to build and train unconditional diffusion model from scratch ?

Lecture 2: How to use any pretrained diffusion model from Hugging Face Hub ?

Lecture 3: How can we do Inpaint using our diffusion model?

Lecture 4: How to implement Repaint algorithm? python code

Lecture 5: How to speed up your diffusion model ?

Lecture 6: DDIM vs DDPM python code

Lecture 7: DDIM and out of domain images

Lecture 8: DDIM and out of domain images python code

Lecture 9: What is style transfer ?

Lecture 10: style transfer python code

Chapter 3: Stable diffusion model

Lecture 1: What is stable diffusion ?

Lecture 2: stable diffusion part 1 python code

Lecture 3: stable diffusion part 2 python code

Lecture 4: Fine-tuning your stable diffusion model using DreamBooth notebook part1

Lecture 5: What is Mixed Precision ?

Lecture 6: Fine-tuning your stable diffusion model using DreamBooth notebook part2

Lecture 7: What is ControlNet ?

Lecture 8: ControlNet with stable diffusion model using diffusers

Lecture 9: Inpainting with stable diffusion model

Chapter 4: Video to AI Animation with stable diffusion from scratch [New]

Lecture 1: Optical flow using FlowNet

Lecture 2: Optical flow using GMFlow

Lecture 3: Optical flow using GMFlow ?python code

Lecture 4: How to convert your video into frames ?python code

Lecture 5: How to extract the latents ? python code

Lecture 6: How to find the canny inputs and the latents for each key-frame ? python code

Lecture 7: How to generate new key-frames using sd model with control net ? python code

Lecture 8: What is cross frame-attention ?

Lecture 9: How to do cross-frame attention part1 ? python code

Lecture 10: How to do cross-frame attention part2 ? python code

Lecture 11: How to make your generated key-frames sharing the same textures ?

Lecture 12: Shape-aware module python code

Lecture 13: Pixel-Aware module

Lecture 14: Pixel-Aware module python code

Lecture 15: How to do keyframes to animation?

Chapter 5: EMO: Emote Portrait Alive [New]

Lecture 1: EMO introduction

Lecture 2: EMO introduction part2

Lecture 3: backbone NN

Lecture 4: How to inject an audio file in the U network ?

Lecture 5: What are ReferenceNet.& Temporal Modules ?

Lecture 6: What is Speed layer and Face locator ?

Chapter 6: Portrait Image Animation

Lecture 1: How the model works ?

Lecture 2: let's try it !!!

Chapter 7: Recap [New]

Lecture 1: what is diffusers library ?

Lecture 2: how to create a pipeline object and how to use it ?

Lecture 3: how these pipelines work ?

Lecture 4: How to use the same diffusion model to do different tasks ?

Lecture 5: How to select the best scheduler ?

Lecture 6: How to use lora models ?

Lecture 7: How to use lora models ? part2

Lecture 8: How to use AnimateDiff pipeline?

Lecture 9: How to use AudioDML pipeline?

Lecture 10: How to use depthmap controlnet with your sd model ?

Chapter 8: AUTOMATIC1111

Lecture 1: How to install AUTOMATIC1111 on Windows ?

Lecture 2: How to add your stable diffusion models & control nets in AUTOMATIC1111 ?

Lecture 3: txt2img in AUTOMATIC1111

Lecture 4: What are LoRA models ?

Lecture 5: How to train stable difusion models using LoRA method?

Lecture 6: img2img + inpainting + outpainting

Lecture 7: sketch + inpaint sketch

Lecture 8: How to create good prompt ?

Lecture 9: What is Regional Prompter ?

Lecture 10: Dynamic prompts

Lecture 11: open pose Controlnet

Lecture 12: How to upscale your image using controlnet ?

Lecture 13: How to use multi controlNets ?

Lecture 14: How to do perfect fingers ?

Lecture 15: How to use photopea editor in AUTOMATIC1111 ?

Lecture 16: control lighting with controlnet

Lecture 17: How to do zoom in and zoom out in automatic 1111 ?

Lecture 18: How can you convert your video into animation ??