Vertex AI Generative Media Training in Copenhagen, Denmark

The Vertex AI Generative Media Training is a hands-on program designed to teach how to use Google Cloud Vertex AI to generate, customize, and deploy AI-powered media content, including images, video, audio, and multimodal assets.

The course focuses on integrating generative media models into applications and workflows, enabling teams to build scalable, secure, and production-ready generative media solutions on Google Cloud.

Introduction to Generative Media on Vertex AI

• Overview of generative media use cases
• Vertex AI generative model ecosystem
• Media generation vs traditional creative tools
• Enterprise and creative industry applications

Vertex AI Generative Media Architecture

• Vertex AI service architecture
• Media model endpoints
• Authentication and access control
• Cost and scalability considerations

Image Generation with Vertex AI

• Text-to-image fundamentals
• Image style, composition, and control
• Variations, edits, and inpainting
• Image quality and resolution handling

Video Generation & Media Workflows

• Video generation concepts
• Frame and scene generation
• Storyboard-style workflows
• Video pipeline orchestration

Audio & Speech Generation

• Text-to-speech and voice generation
• Audio style and tone control
• Audio integration in applications
• Accessibility and voice use cases

Multimodal Prompts & Inputs

• Combining text, image, and audio inputs
• Multimodal prompt design
• Cross-modal understanding
• Advanced creative workflows

Media Prompt Engineering

• Prompting for visual composition
• Prompting for style and branding
• Iterative prompt refinement
• Reusable media prompt templates

Media Editing & Customization

• Image editing and transformations
• Background removal and replacement
• Branding and asset customization
• Batch media processing

Building Generative Media Pipelines

• Media workflow orchestration
• Batch vs real-time generation
• Automation with cloud services
• Media asset management integration

Content Safety, Moderation & Policy Controls

• Responsible AI for media
• Safety filters and moderation
• Copyright and brand protection concepts
• Enterprise content governance

Performance, Cost & Scaling

• Media generation performance tuning
• Cost optimization strategies
• Handling high-volume media generation
• Caching and reuse

Integration with Applications & Platforms

• Embedding generative media in web apps
• Mobile and backend integration
• CMS and DAM system integration
• API gateway and security patterns

Testing & Quality Assurance for Media AI

• Evaluating media quality
• Consistency and brand checks
• Automated QA for generated assets
• Human review workflows

Deployment & Production Operations

• CI/CD for generative media pipelines
• Monitoring and observability
• Versioning prompts and assets
• Rollback and change management

Hands-on Exercises

Summary and Conclusion