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Course Outline
Overview of Multimodal Capabilities in Gemini 3
- Understanding functionality across text, imagery, audio, and video
- Guidance on model selection and available endpoints
- Foundational principles of multimodal reasoning
Handling Text and Structured Data
- Strategies for effective text generation prompting
- Managing metadata, context windows, and embeddings
- Orchestrating multimodal tasks via text-based logic
Visual Analysis and Image Workflows
- Performing image analysis and interpretation using Gemini 3
- Developing tools for visual search and automatic tagging
- Implementing bidirectional interactions between images and text
Processing Audio Inputs
- Workflows for speech recognition and transcription
- Detecting and interpreting specific audio events
- Combining audio signals with text and visual data streams
Video Intelligence and Scene Analysis
- Applying both frame-by-frame and continuous reasoning to video
- Creating tools for content summarization and highlight extraction
- Utilizing video data for automation and content pipelines
Architecting Multimodal Applications
- Integrating diverse input types into a single processing pipeline
- Considerations for latency, cost, and computational resources
- Best practices for building scalable multimodal systems
Building Multimodal Prototypes
- Practical sessions on creating multimodal application prototypes
- Refining solutions through rapid iteration and prompt engineering
- Testing and optimizing user experience flows
Deployment of Multimodal Solutions
- Setup of environments and deployment strategies
- Monitoring performance in production environments
- Addressing security and compliance requirements
Recap and Future Directions
Requirements
- A solid grasp of modern AI concepts
- Practical experience with Python or JavaScript
- Working knowledge of REST APIs
Target Audience
- Designers
- Content creators
- Technical product teams
14 Hours
Testimonials (1)
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