EulerFold
Generative AI Practitioners

Fine-tuning Diffusion Models (DreamBooth & LoRA)

4 weeks
0 Learners
Jul 23

Inject custom subjects into Stable Diffusion or Flux without retraining the full model. This comprehensive curriculum is designed to give you hands-on experience with Fine-tuning Diffusion Models (DreamBooth & LoRA).

Share:

About this Course

Inject custom subjects into Stable Diffusion or Flux without retraining the full model. This comprehensive curriculum is designed to give you hands-on experience with Fine-tuning Diffusion Models (DreamBooth & LoRA). This Generative AI Practitioners curriculum is designed to give you hands-on experience and deep conceptual understanding. Across 4 intensive modules, you'll tackle real-world challenges and build practical projects that reinforce your learning. By the end of this journey, you'll have the skills and proof of work to demonstrate your expertise.

What you'll learn

Master the core concepts of latent diffusion architecture & text-to-image.
Gain hands-on experience with dreambooth fine-tuning & subject preservation.
Understand the architecture behind low-rank adaptation (lora) for diffusion pipelines.
Implement production-grade dataset curation, training & quantization.

Prerequisites

intermediate Level

Requires basic familiarity with the tech stack.

  • Python scripting
  • Basic linear algebra & tensors

Ideal for

Generative AI Practitioners

Generative AI Practitioners Professionals
Tech Enthusiasts
W1

Latent Diffusion Architecture & Text-to-Image

Master the core concepts of latent diffusion architecture & text-to-image.

3 videos80m
3 readings
3 topics
1 homework
Learn

Topics

1.1
Latent Space & VAE Encoders
14 minutes
1.2
UNet Architecture & Cross-Attention
57 minutes
1.3
Noise Schedules & Denoising Timesteps
9 minutes
W2

DreamBooth Fine-Tuning & Subject Preservation

Gain hands-on experience with dreambooth fine-tuning & subject preservation.

3 videos63m
3 readings
3 topics
1 homework
Learn
W3

Low-Rank Adaptation (LoRA) for Diffusion Pipelines

Understand the architecture behind low-rank adaptation (lora) for diffusion pipelines.

3 videos76m
2 readings
3 topics
1 homework
Learn
W4

Dataset Curation, Training & Quantization

Implement production-grade dataset curation, training & quantization.

3 videos60m
3 readings
3 topics
1 homework
Learn
01

Learn

Watch curated videos and read study resources

02

Practice

Practice what you learned

03

Build Projects

Build projects using your new gained knowledge

04

Submit & Verify

Submit your project and get verified by our system

Rate this course

0.0
0 reviews

Help the community find verified technical paths.

Community Insights

0

Join the discussion

Sign in to share your thoughts and technical insights.

Loading insights...