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Duration 14 hours
Course Outline
Foundations of Gemini 3 Multimodality
- Core capabilities spanning text, images, audio, and video
- Model selection strategies and endpoint landscapes
- Fundamental principles of multimodal reasoning
Handling Text and Structured Data
- Advanced prompting strategies for text generation
- Managing metadata, context windows, and embeddings
- Orchestrating multimodal tasks via text-based logic
Image Analysis and Visual Processing
- Interpreting and analyzing images with Gemini 3
- Developing tools for visual search and automated tagging
- Implementing bidirectional image-to-text and text-to-image workflows
Processing Audio Inputs
- Workflows for speech recognition and transcription
- Detection and interpretation of audio events
- Synthesizing audio data with text and visual inputs
Video Intelligence and Scene Interpretation
- Continuous and frame-based video reasoning
- Creating tools for content summarization and highlight extraction
- Automating video-based content workflows
Architecting Multimodal Applications
- Unifying multiple input modalities within a single pipeline
- Evaluating latency, cost, and computational efficiency
- Best practices for designing scalable multimodal systems
Developing Multimodal Prototypes
- Practical creation of functional multimodal prototypes
- Accelerating iteration cycles through prompt engineering
- Testing and polishing user experience interactions
Deployment of Multimodal Solutions
- Strategic deployment plans and environment configuration
- Tracking and analyzing real-world performance metrics
- Addressing security and compliance requirements
Conclusion and Future Directions
Requirements
- A solid grasp of contemporary AI concepts
- Proficiency in Python or JavaScript
- Knowledge of REST API architecture
Target Audience
- Designers
- Content creators
- Technical product teams
Testimonials (1)
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