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Course Outline
Introduction to Gemini 3 Multimodality
- Capabilities spanning text, images, audio, and video
- Model selection and an overview of endpoints
- Core concepts in multimodal reasoning
Working with Text and Structured Inputs
- Strategies for effective text generation prompting
- Managing metadata, context windows, and embeddings
- Orchestrating multimodal tasks through text-based commands
Image Understanding and Visual Workflows
- Analyzing and interpreting images with Gemini 3
- Developing visual search and tagging utilities
- Creating image-to-text and text-to-image interactions
Audio Input Processing
- Workflows for speech recognition and transcription
- Detecting and interpreting audio events
- Merging audio with text and visual inputs
Video Intelligence and Scene Analysis
- Reasoning through frame-by-frame and continuous video
- Building tools for summarization and highlight extraction
- Implementing video-based automation and content workflows
Designing Multimodal Application Architectures
- Combining multiple input types within a single pipeline
- Considering latency, cost, and computational requirements
- Best practices for building 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 configuration
- Monitoring performance in real-world scenarios
- Addressing security and compliance considerations
Summary and Next Steps
Requirements
- A solid understanding of modern AI concepts
- Practical experience with Python or JavaScript
- Working knowledge of REST APIs
Audience
- Designers
- Content creators
- Technical product teams
14 Hours
Testimonials (1)
Flow , vibe and topic on presentation