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Duration 14 hours
Course Outline
Foundations of Gemini 3 Multimodality
- Capabilities spanning text, images, audio, and video
- Guidance on model selection and endpoint landscapes
- Core principles of multimodal reasoning
Managing Text and Structured Inputs
- Effective prompting techniques for text generation
- Handling metadata, context windows, and embeddings
- Orchestrating multimodal tasks via text-based logic
Image Analysis and Visual Processing
- Analyzing and interpreting images with Gemini 3
- Developing visual search and tagging utilities
- Creating bidirectional image-to-text and text-to-image interactions
Audio Data Processing
- Workflows for speech recognition and transcription
- Detecting and interpreting audio events
- Synthesizing audio with textual and visual data inputs
Video Intelligence and Scene Analysis
- Applying reasoning to both frame-level and continuous video streams
- Constructing tools for summarization and highlight extraction
- Automating video-based content workflows
Architecting Multimodal Applications
- Merging diverse input types within a single pipeline
- Evaluating latency, cost, and computational impacts
- Best practices for scalable multimodal system design
Prototyping Multimodal Solutions
- Building functional multimodal prototypes from scratch
- Accelerating iteration cycles through prompt engineering
- Validating and refining user experience journeys
Deploying Multimodal Systems
- 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
- Working knowledge of REST APIs
Target Audience
- Designers
- Content creators
- Technical product teams
Testimonials (1)
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