Multimodal Applications with Gemini 3: Vision, Audio, Video & Text Training Course
Gemini 3 is a multimodal AI platform capable of processing and reasoning across images, video, audio, and text.
This instructor-led, live training (online or onsite) is aimed at intermediate-level practitioners who wish to design and build applications that take advantage of Gemini 3’s cross-modal intelligence.
Upon completion of this workshop, participants will gain the ability to:
- Integrate Gemini 3 multimodal endpoints into real-world workflows.
- Process and interpret visual, audio, video, and text inputs in unified pipelines.
- Build interactive prototypes using multimodal prompts.
- Optimize multimodal outputs for performance, accuracy, and usability.
Format of the Course also allows for the evaluation of participants.
- Guided lectures with demonstrations.
- Scenario-based exercises and hands-on practice.
- Practical implementation using live development environments.
Course Customization Options
- For tailored content or custom project-based training, please contact us to arrange.
Course Outline
Introduction to Gemini 3 Multimodality
- Capabilities across text, images, audio, and video
- Model selection and endpoint overview
- Key concepts in multimodal reasoning
Working with Text and Structured Inputs
- Prompting strategies for text generation
- Metadata, context windows, and embeddings
- Text-based orchestration of multimodal tasks
Image Understanding and Visual Workflows
- Image analysis and interpretation with Gemini 3
- Creating visual search and tagging tools
- Building image-to-text and text-to-image interactions
Audio Input Processing
- Speech recognition and transcription workflows
- Audio event detection and interpretation
- Integrating audio with text and visual inputs
Video Intelligence and Scene Analysis
- Frame-by-frame and continuous video reasoning
- Building summarization and highlight extraction tools
- Video-based automation and content workflows
Designing Multimodal Application Architectures
- Combining multiple input types in a single pipeline
- Latency, cost, and computational considerations
- Best practices for scalable multimodal systems
Prototyping Multimodal Applications
- Hands-on creation of multimodal prototypes
- Rapid iteration with prompt engineering
- Testing and refining user experience flows
Deploying Multimodal Solutions
- Deployment strategies and environment setup
- Monitoring real-world performance
- Security and compliance considerations
Summary and Next Steps
Requirements
- An understanding of modern AI concepts
- Experience with Python or JavaScript
- Familiarity with REST APIs
Audience
- Designers
- Content creators
- Technical product teams
Open Training Courses require 5+ participants.
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Lukasz Kowalczyk - Allegro Sp. z o.o.
Course - Google Gemini AI for Data Analysis
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