Multimodal LLM Workflows in Vertex AI Training Course

Introduction to Multimodal LLMs in Vertex AI

• An overview of multimodal capabilities available in Vertex AI.
• Exploration of Gemini models and their supported modalities.
• Real-world use cases in enterprise and research settings.

Setting Up the Development Environment

• Configuring Vertex AI for multimodal workflow development.
• Managing datasets across different modalities.
• Hands-on lab: Setting up the environment and preparing datasets.

Long Context Windows and Advanced Reasoning

• Understanding the mechanics of long-context workflows.
• Applications in planning and complex decision-making.
• Hands-on lab: Implementing and analyzing long-context processes.

Cross-Modal Workflow Design

• Integrating text, audio, and image analysis into a cohesive process.
• Chaining multimodal steps within data pipelines.
• Hands-on lab: Designing a comprehensive multimodal pipeline.

Working with Gemini API Parameters

• Configuring multimodal inputs and outputs.
• Optimizing inference speed and operational efficiency.
• Hands-on lab: Tuning Gemini API parameters for optimal results.

Advanced Applications and Integrations

• Developing interactive multimodal agents and assistants.
• Integrating external APIs and third-party tools.
• Hands-on lab: Building a complete multimodal application.

Evaluation and Iteration

• Testing and assessing multimodal performance.
• Key metrics for accuracy, alignment, and drift detection.
• Hands-on lab: Evaluating and refining multimodal workflows.

Summary and Next Steps