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
- Exploring the core capabilities of Agent Builder
- Understanding RAG fundamentals and applicable scenarios
- Reviewing real-world use cases and success stories
Environment Setup
- Setting up your Vertex AI workspace
- Linking search engines and vector stores
- Practical lab: Preparing your development environment
Designing Grounded Agent Workflows
- Establishing agent objectives and conversation structures
- Aligning data sources with effective retrieval strategies
- Practical lab: Constructing a conversational flow
Building RAG Pipelines
- Indexing documents and generating embeddings
- Applying retriever and re-ranker patterns
- Practical lab: Developing a functional RAG pipeline
Integrations and Enterprise Data
- Establishing secure connections to internal systems
- Implementing data governance and access controls
- Practical lab: Connecting to enterprise data sources
Testing, Evaluation, and Iteration
- Conducting prompt tests and analyzing evaluation metrics
- Utilizing user simulation and validation techniques
- Practical lab: Evaluating and optimizing agent performance
Deployment, Monitoring, and Maintenance
- Navigating deployment options and scaling factors
- Tracking performance, relevance, and data drift
- Developing operational playbooks for updates and rollbacks
Conclusion and Future Directions
Requirements
- Fundamental understanding of natural language processing
- Hands-on experience with cloud platforms and API interactions
- Working knowledge of search engines and vector databases
Target Audience
- Software developers
- Solution architects
- Product managers
14 Hours
