Building Smart Agents with Vertex AI Agent Builder & RAG Training Course

Overview of Agent Builder and RAG Concepts

• Examining the core capabilities of Agent Builder.
• Explaining RAG fundamentals and appropriate use cases.
• Reviewing real-world applications and success stories.

Environment Configuration

• Setting up the Vertex AI workspace.
• Establishing connections to search and vector stores.
• Practical exercise: Preparing the development environment.

Creating Grounded Agent Workflows

• Defining agent objectives and conversational structures.
• Aligning data sources with retrieval methods.
• Practical exercise: Constructing a conversation flow.

Building RAG Pipelines

• Processing documents and generating embeddings.
• Applying retriever and re-ranker patterns.
• Practical exercise: Assembling a RAG pipeline.

Enterprise Integrations and Data Handling

• Setting up secure links to internal systems.
• Managing data governance and access permissions.
• Practical exercise: Linking enterprise data sources.

Testing, Assessment, and Improvement

• Conducting prompt tests and analyzing evaluation metrics.
• Simulating user interactions for validation.
• Practical exercise: Testing and optimizing agent behavior.

Deployment, Surveillance, and Upkeep

• Reviewing deployment choices and scaling strategies.
• Monitoring system performance, relevance, and drift.
• Creating operational plans for updates and rollbacks.

Wrap-up and Future Directions