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Course Outline
Introduction to Gemini 3 Multimodality
- Exploring capabilities across text, images, audio, and video
- Overview of model selection and 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 inputs
Image Understanding and Visual Workflows
- Analyzing and interpreting images with Gemini 3
- Developing tools for visual search and tagging
- Creating interactions between image-to-text and text-to-image
Audio Input Processing
- Implementing speech recognition and transcription workflows
- Detecting and interpreting audio events
- Integrating audio data with text and visual inputs
Video Intelligence and Scene Analysis
- Conducting frame-by-frame and continuous video reasoning
- Building tools for summarization and highlight extraction
- Automating content workflows using video data
Designing Multimodal Application Architectures
- Combining multiple input types within a single pipeline
- Addressing latency, cost, and computational factors
- Applying 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 configuration
- Monitoring real-world performance metrics
- Addressing security and compliance requirements
Summary and Next Steps
Requirements
- A foundational understanding of modern AI concepts
- Prior experience with Python or JavaScript
- Familiarity with REST APIs
Target Audience
- Designers
- Content creators
- Technical product teams
14 Hours
Testimonials (1)
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