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Course Outline
Introduction to Gemini 3 Multimodality
- Capabilities spanning text, images, audio, and video
- Model selection and endpoint overview
- Core principles of multimodal reasoning
Managing Text and Structured Inputs
- Strategies for effective text generation prompting
- Handling metadata, context windows, and embeddings
- Orchestrating multimodal tasks via text-based logic
Image Understanding and Visual Workflows
- Analyzing and interpreting images with Gemini 3
- Developing visual search and tagging utilities
- Creating interactions between image-to-text and text-to-image
Processing Audio Inputs
- Workflows for speech recognition and transcription
- Detecting and interpreting audio events
- Synthesizing audio with textual and visual data
Video Intelligence and Scene Analysis
- Reasoning through frame-by-frame and continuous video streams
- Creating tools for summarization and highlight extraction
- Automating video-based processes and content workflows
Architecting Multimodal Applications
- Merging multiple input types into a single pipeline
- Considering latency, costs, and computational resources
- Best practices for building scalable multimodal systems
Prototyping Multimodal Applications
- Hands-on development of multimodal prototypes
- Iterating rapidly through prompt engineering
- Testing and refining user experience pathways
Deploying Multimodal Solutions
- Strategies for deployment and environment configuration
- Monitoring performance in live environments
- Addressing security and compliance requirements
Conclusion and Future Directions
Requirements
- A solid grasp of contemporary AI principles
- Proficiency in Python or JavaScript
- Working knowledge of REST APIs
Target Audience
- Designers
- Content creators
- Technical product teams
14 Hours
Testimonials (1)
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