Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Introduction to Agent Builder and RAG
- Overview of Agent Builder capabilities
- RAG fundamentals and appropriate use cases
- Real-world examples and success stories
Environment Setup
- Configuring the Vertex AI workspace
- Connecting search and vector stores
- Hands-on lab: preparing the environment
Designing Grounded Agent Workflows
- Defining agent objectives and conversation flows
- Mapping data sources to retrieval strategies
- Hands-on lab: constructing a conversation flow
Implementing RAG Pipelines
- Indexing documents and embeddings
- Retriever and re-ranker patterns
- Hands-on lab: building a RAG pipeline
Integrations and Enterprise Data
- Secure connectors for internal systems
- Data governance and access controls
- Hands-on lab: connecting enterprise data sources
Testing, Evaluation, and Iteration
- Prompt testing and evaluation metrics
- User simulation and validation strategies
- Hands-on lab: assessing and tuning the agent
Deployment, Monitoring, and Maintenance
- Deployment options and scaling considerations
- Monitoring performance, relevance, and drift
- Operational playbooks for updates and rollback
Summary and Next Steps
Requirements
- Fundamental understanding of natural language processing.
- Hands-on experience with cloud services and APIs.
- Familiarity with search engines and vector databases.
Target Audience
- Developers
- Solution architects
- Product managers
14 Hours
