Multimodal LLM Workflows in Vertex AI Training Course

Introduction to Multimodal LLMs in Vertex AI

• Exploring multimodal capabilities available in Vertex AI
• Overview of Gemini models and their supported modalities
• Real-world applications in enterprise and research sectors

Configuring the Development Environment

• Setting up Vertex AI for multimodal workflow operations
• Managing datasets that span multiple modalities
• Practical lab: Environment configuration and dataset preparation

Long Context Windows and Advanced Reasoning

• Concepts behind long-context workflow implementation
• Applications in complex planning and decision-making processes
• Practical lab: Executing long-context analytical tasks

Cross-Modal Workflow Architecture

• Synthesizing text, audio, and image analysis components
• Sequencing multimodal stages within pipeline architectures
• Practical lab: Designing a comprehensive multimodal pipeline

Managing Gemini API Parameters

• Configuring multimodal input and output settings
• Enhancing inference speed and operational efficiency
• Practical lab: Fine-tuning Gemini API parameters for optimal results

Advanced Applications and System Integrations

• Developing interactive multimodal agents and assistants
• Connecting external APIs and third-party tools
• Practical lab: Building a functional multimodal application

Evaluation Strategies and Iterative Improvement

• Assessing the performance of multimodal systems
• Applying metrics for accuracy, alignment, and drift detection
• Practical lab: Conducting performance evaluations on multimodal workflows

Wrap-up and Future Directions