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Duration 14 hours
Course Outline
Introduction to Gemini 3 Multimodality
- Capabilities spanning text, images, audio, and video
- Model selection and endpoint overview
- Core concepts in multimodal reasoning
Working with Text and Structured Inputs
- Prompting strategies for effective text generation
- Metadata, context windows, and embeddings
- Orchestrating multimodal tasks using text
Image Understanding and Visual Workflows
- Analyzing and interpreting images with Gemini 3
- Creating tools for visual search and tagging
- Building interactions between image-to-text and text-to-image
Audio Input Processing
- Workflows for speech recognition and transcription
- Detecting and interpreting audio events
- Integrating audio with text and visual inputs
Video Intelligence and Scene Analysis
- Frame-by-frame and continuous video reasoning
- Developing tools for summarization and highlight extraction
- Automation and content workflows based on video
Designing Multimodal Application Architectures
- Combining multiple input types within a single pipeline
- Considerations for latency, cost, and computation
- Best practices for scalable multimodal systems
Prototyping Multimodal Applications
- Hands-on development of multimodal prototypes
- Rapid iteration through prompt engineering
- Testing and refining user experience flows
Deploying Multimodal Solutions
- Deployment strategies and environment setup
- Monitoring performance in real-world scenarios
- Addressing security and compliance considerations
Summary and Next Steps
Requirements
- A solid understanding of modern AI concepts
- Proficiency in Python or JavaScript
- Familiarity with REST APIs
Target Audience
- Designers
- Content creators
- Technical product teams
Testimonials (1)
Flow , vibe and topic on presentation
