Mastering AI Video Generation: Google VEO vs OpenAI Sora – Concepts, Comparisons & Creative Use Cases
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Training TypeLive Training
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CategoryArtificial Intelligence
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Duration3 Hours
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Rating4.9/5
Course Introduction
About the Course
This course dives deep into the two most powerful generative video models in the world today - Google VEO and OpenAI Sora. You’ll explore how they work, what differentiates them, how to craft effective prompts, and what business and creative opportunities they unlock.
Designed for learners who want to understand AI-powered video creation, this course simplifies complex underlying architectures, compares model capabilities, and provides hands-on use case simulations that demonstrate real-world value.
Course Objective
By the end of this course, you will be able to:
Understand the fundamental concepts behind generative video models
Explain how Google VEO and OpenAI Sora differ in terms of architecture, capabilities, and output
Identify appropriate use cases for each model (ads, storytelling, education, etc.)
Craft effective prompts for high-quality video generation
Understand the limitations, ethical issues, and deployment challenges
Stay ahead with trends and the potential future of AI video generation
Who is the Target Audience?
This course is designed for:
Content Creators & Marketers – looking to create AI-generated visual stories, ads, or product explainers
AI Enthusiasts & Developers – who want to learn how cutting-edge video generation models work
Educators & Trainers – to create interactive, AI-generated visual learning assets
Game Designers & Filmmakers – interested in pre-visualization and AI-driven creative design
Product Managers & Entrepreneurs – exploring video AI integration in their workflows or SaaS tools
Basic Knowledge
Basic understanding of Artificial Intelligence and Machine Learning concepts
Familiarity with terms like text-to-image, diffusion models, or transformers (helpful but not mandatory)
No coding knowledge is required, but a curiosity about AI creativity tools is a must
Optional: Knowledge of tools like Midjourney, RunwayML, or D-ID will help learners appreciate how VEO/Sora compare
Available Batches
| 09 Jul 2025 | Wed ( 1 Day ) | 12:00 PM - 03:00 PM (Eastern Time) |
| 06 Aug 2025 | Wed ( 1 Day ) | 12:00 PM - 03:00 PM (Eastern Time) |
| 10 Sep 2025 | Wed ( 1 Day ) | 12:00 PM - 03:00 PM (Eastern Time) |
Pricing
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What is Generative Video AI?
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Evolution: From GANs to Diffusion to Sora/VEO
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Why it matters now: Video + AI Convergence
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Key Challenges in Video Generation: Temporal Coherence, Frame Quality, Resolution
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What is Google VEO?
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Architecture & Model Components (Imagen Video + Lumiere)
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Long-form video
Cinematic quality
Multiple input modalities (text, image, reference video)
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Example Prompts and Visual Outputs
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Limitations & Optimization Areas
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Use Cases (Ad creation, Film pre-visualization, Training videos)
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Quality & Fidelity (Resolution, Frame Rate, Scene Stability)
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Prompt Versatility & Input Modalities
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Rendering Time & Performance
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Output Duration and Realism
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Use Case Fit: Which to Use When?
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Current Availability (API/Closed Access?)
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Diffusion Models: Simplified Explanation
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Temporal Latents and Frame Interpolation
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Scene Conditioning: Text → Scene + Action
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Limitations in AI Understanding of Motion
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Future of Video LLMs
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Prompt Design for Sora (Examples, Best Practices)
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Prompt Design for Google VEO
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Creating a scene step-by-step from a prompt
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Simulating Use Cases via mock APIs or visual walkthroughs
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Building a Prompt Template Library
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Deepfakes vs Creativity
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Content Authenticity & Watermarking
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Ownership, Licensing, and Copyright
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Responsible Use in Education & Marketing
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Trends in Generative Video AI
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Where the industry is heading
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Skillsets needed to thrive in this field
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Resources for Continued Learning (Research papers, APIs, tools)