Building Smart Agents with Vertex AI Agent Builder & RAG Training Course
Vertex AI Agent Builder provides a no-code and low-code environment for developing grounded agents that integrate generative models with retrieval-augmented generation (RAG). This capability enables organizational teams to rapidly construct intelligent agents that leverage enterprise data and search capabilities to deliver accurate, context-aware responses. The resulting solutions are optimized for government applications and complex operational requirements.
This instructor-led, live training, available in online or onsite formats, is designed for intermediate-level practitioners seeking to design, configure, and deploy intelligent agents using Vertex AI Agent Builder and established RAG patterns.
Upon completion of this instruction, participants will be equipped to:
* Design grounded agent workflows utilizing Agent Builder.
* Implement RAG pipelines integrated with search services and vector stores.
* Securely integrate enterprise data sources to facilitate accurate retrieval.
* Evaluate and iterate agent performance through systematic testing and metrics analysis.
**Course Format**
* Interactive lectures and professional discussions.
* Practical laboratory exercises utilizing Vertex AI Agent Builder and RAG components.
* Project-based assignments to construct and refine agent capabilities.
**Course Customization Options**
* To arrange customized training for this course, please contact the training provider to discuss specific organizational needs.This course is available as onsite live training in US Government or online live training.
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Course Outline
Overview of Agent Builder and Retrieval-Augmented Generation
- Capabilities overview of Agent Builder
- Core principles of Retrieval-Augmented Generation (RAG) and applicable scenarios
- Strategic use cases and documented outcomes
Environment Configuration
- Vertex AI workspace setup
- Integration of search and vector storage systems
- Practical exercise: establishing the operational environment
Architecting Grounded Agent Workflows
- Establishing agent objectives and dialogue sequences
- Aligning data sources with retrieval methodologies
- Practical exercise: constructing a dialogue workflow
Developing RAG Pipelines
- Document indexing and embedding generation
- Implementation of retriever and re-ranking protocols
- Practical exercise: deploying a RAG pipeline
Enterprise Data Integrations
- Secure connectivity to internal agency systems
- Data governance frameworks and access control policies
- Practical exercise: linking enterprise data repositories
Testing, Evaluation, and Continuous Improvement
- Prompt assessment and performance metrics
- User simulation techniques and validation strategies
- Practical exercise: assessing and optimizing agent performance
Deployment, Monitoring, and Lifecycle Management
- Deployment architectures and scalability considerations
- Tracking performance, accuracy, and model drift
- Operational guidelines for updates and contingency rollback
Conclusion and Future Actions
Requirements
* Foundational understanding of natural language processing principles
* Demonstrated proficiency in utilizing cloud-based services and application programming interfaces
* Working knowledge of search mechanisms and vector data storage systems
**Intended Audience**
* Software development personnel
* Solution architecture professionals
* Product management stakeholders
Designed for government
14 Hours
Runs with a minimum of 4 + people. For 1-to-1 or private group training, request a quote.
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