You’ve built a governed data foundation, prepared curated data, and automated data workflows. Now you’re ready to build and deploy AI agents that use trusted data and policy information to support defined business tasks.
The fourth e-learning module in the Oracle AI Data Platform Essentials series, Build and Deploy AI Agents in Oracle AI Data Platform, shows you how to design, build, test, deploy, and integrate AI agents. Using an expense-compliance scenario, you’ll connect curated expense data and policy documents to agent tools, test agent behavior, and prepare an agent for use in a managed environment.
In this course, you’ll learn how to:
- Explain core AI agent components and common business use cases.
- Design an agent with clear responsibilities, suitable models and tools, memory and state boundaries, and guardrails.
- Build an agent in the visual editor using tools that connect to structured data and knowledge sources.
- Build that same agent using the Code editor.
- Test and refine agent behavior in the Playground by reviewing traces, spans, tool calls, and answer quality.
- Prepare an agent for deployment, monitoring, and integration, including authentication, session retention, A2A, and agent-card considerations.
Why this matters
AI agents are most useful when they are built on trusted data, operate within clear boundaries, and can be tested and monitored throughout their lifecycle. This course gives you a practical framework for creating agents that use data and tools responsibly to support real business outcomes.
Who should take this course?
This module is ideal for data professionals, AI developers, and solution implementers who have completed the first three courses in the Oracle AI Data Platform Essentials series or have equivalent experience with AI Data Platform data, permissions, credentials, and workspaces. Familiarity with generative AI and agent concepts is helpful.
Select this link to access the course: Build and Deploy AI Agents in Oracle AI Data Platform.
