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Duration 14 hours
Course Outline
Introduction to Gemini 3 Multimodality
- Overview of capabilities across text, images, audio, and video
- Guidance on model selection and endpoint architecture
- Core principles of multimodal reasoning
Working with Text and Structured Inputs
- Advanced prompting strategies for effective text generation
- Managing metadata, context windows, and embeddings
- Orchestrating multimodal tasks through text-based directives
Image Understanding and Visual Workflows
- Analyzing and interpreting images using Gemini 3
- Developing visual search and automated tagging tools
- Building bidirectional image-to-text and text-to-image interactions
Audio Input Processing
- Implementing speech recognition and transcription workflows
- Detecting and interpreting specific audio events
- Synthesizing audio inputs with text and visual data
Video Intelligence and Scene Analysis
- Performing both frame-by-frame and continuous video reasoning
- Creating tools for video summarization and highlight extraction
- Automating video-based content workflows
Designing Multimodal Application Architectures
- Combining multiple input types within a single, cohesive pipeline
- Evaluating latency, cost, and computational efficiency
- Applying best practices for building scalable multimodal systems
Prototyping Multimodal Applications
- Hands-on development of functional multimodal prototypes
- Accelerating iteration cycles through refined prompt engineering
- Testing and optimizing user experience flows
Deploying Multimodal Solutions
- Formulating deployment strategies and configuring environments
- Monitoring performance metrics in production settings
- Addressing security and compliance requirements
Summary and Future Directions
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)
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