Get in Touch
 Duration 14 hours

Course Outline

Introduction to Agent Builder and Retrieval-Augmented Generation (RAG)

  • Summary of Agent Builder features and capabilities
  • Foundational concepts of RAG and applicable scenarios
  • Operational use cases and documented outcomes

Establishing the Technical Environment

  • Configuration of the Vertex AI workspace
  • Integration of search services and vector storage systems
  • Practical exercise: Preparation of the technical environment

Architecting Grounded Agent Workflows

  • Specification of agent objectives and interaction logic
  • Alignment of data sources with retrieval methods
  • Practical exercise: Development of a conversational flow

Deployment of RAG Pipelines

  • Indexation of documents and creation of embeddings
  • Patterns for retrievers and re-rankers
  • Practical exercise: Construction of a RAG pipeline

Enterprise Integration and Data Management

  • Secure connectivity to internal organizational systems
  • Data governance standards and access control protocols
  • Practical exercise: Connection of enterprise data sources

Testing, Assessment, and Optimization

  • Prompt validation and evaluation metrics
  • Strategies for user simulation and performance verification
  • Practical exercise: Assessment and refinement of agent behavior

Deployment, Oversight, and Sustained Operations

  • Deployment strategies and scalability considerations
  • Monitoring of performance, relevance, and data drift
  • Operational protocols for updates and rollback procedures

Conclusion and Future Actions

Requirements

  • Foundational understanding of natural language processing
  • Practical experience with cloud services and API interactions
  • Working knowledge of search and vector databases

Intended Audience

  • Software developers
  • Solution architects
  • Product managers

Number of participants


Price per participant

Upcoming Courses

Related Categories