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Duration 14 hours
Course Outline
Foundations of Gemini 3 Multimodality
- Core capabilities spanning text, images, audio, and video
- Overview of model selection and available endpoints
- Essential concepts in multimodal reasoning
Handling Text and Structured Data
- Advanced prompting strategies for text generation
- Managing metadata, context windows, and embeddings
- Orchestrating multimodal tasks through text-based logic
Image Interpretation and Visual Processes
- Analyzing and interpreting images with Gemini 3
- Developing tools for visual search and tagging
- Implementing bidirectional image-to-text and text-to-image interactions
Processing Audio Inputs
- Workflows for speech recognition and transcription
- Detecting and interpreting audio events
- Merging audio streams with textual and visual data
Video Intelligence and Scene Analysis
- Applying frame-by-frame and continuous video reasoning
- Crafting tools for summarization and highlight extraction
- Automating video-based content workflows
Architecting Multimodal Systems
- Synthesizing multiple input types within a single pipeline
- Evaluating latency, cost, and computational efficiency
- Best practices for scalable multimodal infrastructure
Developing Multimodal Prototypes
- Practical creation of multimodal application prototypes
- Achieving rapid iteration through prompt engineering
- Testing and optimizing user experience flows
Implementing Multimodal Solutions
- Deployment strategies and environment configuration
- Monitoring performance in production environments
- Addressing security and compliance requirements
Conclusion and Future Directions
Requirements
- A solid grasp of contemporary AI concepts
- Proficiency in Python or JavaScript
- Working knowledge of REST APIs
Target Audience
- Designers
- Content creators
- Technical product teams
Testimonials (1)
Flow , vibe and topic on presentation