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.
Duration 14 hours
Course Outline
Foundations of Agent Builder and RAG
- Exploring the core capabilities of Agent Builder
- Key RAG concepts and optimal application scenarios
- Real-world use cases and success stories
Configuring the Development Environment
- Setting up your Vertex AI workspace
- Linking search engines and vector stores
- Practical lab: preparing the environment
Creating Grounded Agent Workflows
- Defining agent objectives and conversational paths
- Aligning data sources with effective retrieval strategies
- Practical lab: constructing a conversation flow
Building RAG Pipelines
- Processing documents and generating embeddings
- Applying retriever and re-ranker patterns
- Practical lab: assembling a RAG pipeline
Enterprise Data Integration
- Establishing secure connections to internal systems
- Implementing data governance and access controls
- Practical lab: connecting enterprise data sources
Testing, Assessment, and Refinement
- Conducting prompt testing and analyzing evaluation metrics
- Employing user simulation and validation techniques
- Practical lab: assessing and tuning agent behavior
Deployment, Oversight, and Maintenance
- Reviewing deployment options and scalability factors
- Monitoring performance, relevance, and data drift
- Developing operational guides for updates and rollbacks
Recap and Future Directions
Requirements
- Fundamental understanding of natural language processing
- Prior experience with cloud platforms and API integrations
- Working knowledge of search technologies and vector databases
Target Audience
- Software Developers
- Solution Architects
- Product Managers
