Large Multimodal Model Prompting with Gemini

What You'll Learn

• Learn state-of-the-art techniques for getting the most out of multimodal AI with Google’s Gemini model family.
• Leverage Gemini’s cross-modal attention to fuse information from text, images, and video for complex reasoning tasks.
• Extend Gemini’s capabilities with external knowledge and live data via function calling and API integration.

About This Course

This course explores how to utilize Google's Gemini model family to build powerful multimodal applications that combine text, images, and videos. Through hands-on examples, you will learn how to optimize prompts, leverage cross-modal reasoning, and integrate real-time data for dynamic and interactive applications.

• Introduction to Gemini Models: Explore the Gemini model family and understand the use cases for different models like Gemini Nano, Pro, Flash, and Ultra.
• Multimodal Prompting and Parameter Control: Learn techniques for structuring effective prompts and adjusting parameters to control model creativity and determinism.
• Best Practices for Multimodal Prompting: Practice prompt engineering techniques like role assignment, task decomposition, and prompt-image ordering.
• Creating Use Cases with Images: Build applications like interior design assistants that utilize Gemini's cross-modal reasoning for complex image analysis.
• Developing Use Cases with Videos: Implement video search and summarization tools by leveraging Gemini’s extensive context window.
• Integrating Real-Time Data with Function Calling: Extend Gemini's capabilities with real-time data and API integration for enhanced functionality.

Note: Due to technical requirements, downloadable notebooks are provided to enable hands-on practice.

Course Outline

• Introduction
  Overview of multimodal AI capabilities with Gemini.
• Introduction to Gemini Models
  Detailed exploration of the Gemini model family and their applications.
• Multimodal Prompting and Parameter Control
  Techniques for creating structured text-image-video prompts and controlling model parameters.
• Best Practices for Multimodal Prompting
  Guidance on optimizing prompt structure, role assignment, and task decomposition.
• Creating Use Cases with Images
  Hands-on examples for building image-based applications.
• Developing Use Cases with Videos
  Techniques for semantic video search and content summarization.
• Integrating Real-Time Data with Function Calling
  Utilizing APIs and live data for dynamic, interactive applications.
• Conclusion
  Recap of course content and best practices.

Who Should Join?

This course is for developers aiming to build advanced multimodal applications using text, images, and videos. Prior experience with AI and basic programming knowledge is recommended.