Multimodal LLM Workflows in Vertex AI Training Course

Introduction to Multimodal LLMs in Vertex AI

• Overview of multimodal capabilities in Vertex AI
• Gemini models and supported modalities
• Use cases in enterprise and research

Setting Up the Development Environment

• Configuring Vertex AI for multimodal workflows
• Working with datasets across modalities
• Hands-on lab: environment setup and dataset preparation

Long Context Windows and Advanced Reasoning

• Understanding long-context workflows
• Use cases in planning and decision-making
• Hands-on lab: implementing long-context analysis

Cross-Modal Workflow Design

• Combining text, audio, and image analysis
• Chaining multimodal steps in pipelines
• Hands-on lab: designing a multimodal pipeline

Working with Gemini API Parameters

• Configuring multimodal inputs and outputs
• Optimizing inference and efficiency
• Hands-on lab: tuning Gemini API parameters

Advanced Applications and Integrations

• Interactive multimodal agents and assistants
• Integrating external APIs and tools
• Hands-on lab: building a multimodal application

Evaluation and Iteration

• Testing multimodal performance
• Metrics for accuracy, alignment, and drift
• Hands-on lab: evaluating multimodal workflows

Summary and Next Steps