Multimodal LLM Workflows in Vertex AI Training Course

Foundations of Multimodal LLMs in Vertex AI

• Overview of multimodal capabilities within Vertex AI
• Introduction to Gemini models and their supported modalities
• Enterprise and research applications

Preparing the Development Environment

• Configuring Vertex AI for multimodal workflows
• Managing datasets across different modalities
• Hands-on lab: setting up the environment and preparing datasets

Long Context Windows and Advanced Reasoning

• Exploring the mechanics of long-context workflows
• Applications in strategic planning and decision-making
• Hands-on lab: executing long-context analysis tasks

Designing Cross-Modal Workflows

• Synthesizing text, audio, and image analytics
• Sequencing multimodal steps within a pipeline
• Hands-on lab: architecting a multimodal pipeline

Configuring Gemini API Parameters

• Setting up multimodal inputs and outputs
• Optimizing inference speed and resource efficiency
• Hands-on lab: fine-tuning Gemini API settings

Advanced Applications and System Integrations

• Building interactive multimodal agents and assistants
• Connecting external APIs and tools
• Hands-on lab: developing a comprehensive multimodal application

Assessment and Continuous Improvement

• Conducting performance tests for multimodal systems
• Tracking metrics for accuracy, alignment, and data drift
• Hands-on lab: evaluating the effectiveness of multimodal workflows

Key Takeaways and Future Directions