Sora: Foundations
Apply Sora through capabilities, limitations, responsible use.
Beginner / Structured learning draft / Version 0.9
Structured learning draftAI Video: Sora & RunwayML
Build a responsible AI workflow for a real work task. You will finish with a documented prompt, verification and revision workflow.
This open learning manuscript is undergoing course-specific editorial review. It does not provide certification. Progress and notes are stored only in this browser.
AI toolsTool stack
OpenAI
12guided lessons
4focused modules
1reviewable project
PDFoffline workbook
The problem
What this course helps you do
AI Video: Sora & RunwayML is a structured, practical course covering Sora, RunwayML, HeyGen. It emphasizes explainable methods, checked work and a final outcome that can be reviewed.
Who it is for
People who want dependable, responsible AI-assisted workflows.
Prerequisites
- Basic computer and web skills
Portfolio-ready project
Produce a reviewable AI Video: Sora & RunwayML project using Sora, RunwayML, HeyGen.
Deliverable: A working AI Video: Sora & RunwayML artefact plus an evidence-based self-review.
Practice fileResponsible AI workflowA source, instruction, review and privacy-check worksheet.Planning template · MarkdownProject briefDefine the user, outcome, boundaries, evidence and acceptance criteria before building.Printable workbook · PDFComplete course workbookA4-ready lesson prompts, project worksheets, evidence logs and references.
Downloads open without an account. Practice data is fictional; review each file before using it in another system.
Definition of done
- The output matches the stated outcome.
- Inputs and decisions are reproducible.
- Boundary and failure evidence is included.
- Limitations and responsibility considerations are explicit.
Course plan
From first concept to finished work
RunwayML: Working methods
Apply RunwayML through clear instructions, context design, verification.
HeyGen: Applied workflows
Apply HeyGen through research, creation, automation.
Sora: Quality and review
Apply Sora through evaluation, privacy, repeatable practice.
Source-led learning
Authoritative references
Course claims are grounded in primary documentation and recognized public guidance. Recheck version-sensitive information before professional use.