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Duration 14 hours
Course Outline
Introduction to Gemini 3 Multimodality
- Capabilities spanning text, images, audio, and video
- Overview of model selection and endpoints
- Fundamental concepts in multimodal reasoning
Handling Text and Structured Inputs
- Effective prompting strategies for text generation
- Managing metadata, context windows, and embeddings
- Orchestrating multimodal tasks via text-based logic
Image Understanding and Visual Workflows
- Analyzing and interpreting images using Gemini 3
- Developing visual search and tagging utilities
- Creating image-to-text and text-to-image interaction flows
Audio Input Processing
- Workflows for speech recognition and transcription
- Detecting and interpreting audio events
- Merging audio with text and visual data streams
Video Intelligence and Scene Analysis
- Reasoning through frame-by-frame and continuous video analysis
- Building tools for summarization and highlight extraction
- Implementing video-based automation and content workflows
Architecting Multimodal Applications
- Integrating multiple input types into a single pipeline
- Addressing latency, cost, and computational efficiency
- Best practices for scaling multimodal systems
Prototyping Multimodal Solutions
- Hands-on development of multimodal prototypes
- Iterating rapidly through prompt engineering
- Testing and polishing user experience flows
Deploying Multimodal Systems
- Deployment strategies and environment configuration
- Monitoring performance in production environments
- Security and compliance considerations
Summary and Next Steps
Requirements
- A solid grasp of modern AI concepts
- Proficiency in Python or JavaScript
- Working knowledge of REST APIs
Target Audience
- Designers
- Content creators
- Technical product teams
Testimonials (1)
Flow , vibe and topic on presentation
