Stable Diffusion Certification

Lessons

1. 1LESSON 1 — STABLE DIFFUSION FUNDAMENTALSDifficulty: Beginner Estimated Time: 35 minutes LEARNING OBJECTIVES Students will learn: What Stable Diffusion is. What diffusion models are. How texttoimage works at a high level.3m
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2. 2LESSON 2 — STABLE DIFFUSION PROMPT ENGINEERINGDifficulty: Beginner → Intermediate Estimated Time: 40 minutes LEARNING OBJECTIVES Students will learn: Positive prompts. Negative prompts. Prompt structure. Subject. Composition. 3m
3. 3LESSON 3 — CHECKPOINTS, MODELS & MODEL MANAGEMENTDifficulty: Intermediate Estimated Time: 45 minutes LEARNING OBJECTIVES Students will learn: Checkpoints. Model families. Base models. Specialized models. Model selection. Model co3m
4. 4LESSON 4 — SAMPLERS, STEPS, CFG, SEEDS & GENERATION SETTINGSDifficulty: Intermediate → Advanced Estimated Time: 50 minutes LEARNING OBJECTIVES Students will learn: Sampling. Sampling steps. CFG. Seeds. Resolution. Batch size. Denoising stre3m
5. 5LESSON 5 — STABLE DIFFUSION IMAGE-TO-IMAGE & DENOISINGDifficulty: Advanced Estimated Time: 45 minutes LEARNING OBJECTIVES Students will learn: Imagetoimage generation. Denoising strength. Reference preservation. Transformation. Sketch3m
6. 6LESSON 6 — INPAINTING, OUTPAINTING & MASKINGDifficulty: Advanced Estimated Time: 45 minutes LEARNING OBJECTIVES Students will learn: Masks. Inpainting. Outpainting. Object replacement. Object removal. Localized editing. Mask3m
7. 7LESSON 7 — CONTROLNET & STRUCTURED IMAGE CONTROLDifficulty: Advanced Estimated Time: 50 minutes LEARNING OBJECTIVES Students will learn: What ControlNet is. Why structural conditioning matters. Edge control. Pose control. Depth 3m
8. 8LESSON 8 — LoRAs, EMBEDDINGS & CUSTOMIZATIONDifficulty: Advanced Estimated Time: 50 minutes LEARNING OBJECTIVES Students will learn: LoRAs. Embeddings. Custom styles. Character customization. Training concepts. Dataset quali3m
9. 9LESSON 9 — ADVANCED STABLE DIFFUSION WORKFLOWS & AUTOMATIONDifficulty: Advanced Estimated Time: 50 minutes LEARNING OBJECTIVES Students will learn: Workflow automation. Nodebased concepts. Reusable pipelines. Batch generation. Prompt varia3m
10. 10LESSON 10 — LOCAL STABLE DIFFUSION, HARDWARE & API DEPLOYMENTDifficulty: Advanced Estimated Time: 50 minutes LEARNING OBJECTIVES Students will learn: Local generation. GPU concepts. VRAM. Storage. Model files. Performance. APIs. Deployment. 3m
11. 11LESSON 11 — STABLE DIFFUSION COPYRIGHT, LICENSING & RESPONSIBLE AIDifficulty: Advanced Estimated Time: 45 minutes LEARNING OBJECTIVES Students will understand: Model licenses. Software licenses. Modelspecific restrictions. Output rights. Dataset 3m
12. 12LESSON 12 — STABLE DIFFUSION MASTERY CAPSTONE & CERTIFICATIONDifficulty: Advanced Estimated Time: 6075 minutes This is the final Stable Diffusion certification lesson. Students must demonstrate practical mastery of the ecosystem.3m
13. 13CAPSTONE OPTIONSOPTION A PROFESSIONAL IMAGE CAMPAIGN Create a complete advertising campaign. OPTION B CHARACTER SYSTEM Create a consistent character across at least four scenes using appropriate c3m
14. 14CAPSTONE REQUIREMENTSStudent must submit: 1. CREATIVE BRIEF Include: Client Audience Objective Deliverables 2. MODEL STRATEGY Explain: Model Why selected Compatibility Alternatives 3. PROMPT STRATEGY P3m
15. 15CAPSTONE SCORINGTotal: 100 points Stable Diffusion Knowledge 20 points Prompt Engineering 15 points Technical Settings 15 points Creative Quality 15 points Control/Customization 10 points Workflow3m
16. 16FINAL EXAM QUESTIONSQUESTION 1 What is Stable Diffusion? A. A single permanent application only\ B. A family/ecosystem of generative image models and workflows\ C. A spreadsheet\ D. An email platform 3m