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Duration 14 hours
Course Outline
Introduction to Gemini 3’s Multimodal Capabilities
- Overview of features across text, images, audio, and video
- Guidance on model selection and endpoint usage
- Fundamental concepts in multimodal reasoning
Handling Text and Structured Data
- Effective prompting strategies for text generation
- Working with metadata, context windows, and embeddings
- Using text to orchestrate multimodal tasks
Image Comprehension and Visual Processes
- Analyzing and interpreting images using Gemini 3
- Developing tools for visual search and tagging
- Implementing interactions between image-to-text and text-to-image
Processing Audio Inputs
- Workflows for speech recognition and transcription
- Detecting and interpreting audio events
- Combining audio with text and visual data
Video Intelligence and Scene Interpretation
- Reasoning on video content, both frame-by-frame and continuously
- Creating tools for summarization and highlight extraction
- Automation and content workflows based on video analysis
Architecting Multimodal Applications
- Merging diverse input types into a unified pipeline
- Evaluating latency, cost, and computational demands
- Best practices for building scalable multimodal systems
Prototyping Multimodal Solutions
- Hands-on development of multimodal prototypes
- Iterating rapidly through prompt engineering
- Testing and refining user experience flows
Deploying Multimodal Solutions
- Strategies for deployment and environment configuration
- Monitoring performance in production environments
- Addressing security and compliance requirements
Wrap-up and Future Directions
Requirements
- A solid grasp of contemporary AI concepts
- Proficiency in Python or JavaScript
- Knowledge of REST API interactions
Target Audience
- Designers
- Content creators
- Technical product teams
Testimonials (1)
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