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Oracle 1z0-1157-26 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Enterprise Agent Development and Governance | - Multi-agent systems and handoffs - Guardrails, agent tracing and monitoring - Function calling and tool integration |
| Topic 2: OCI Enterprise AI Platform | - OCI Enterprise AI services overview - OCI Enterprise AI Agents and Knowledge Bases |
| Topic 3: Agent Fundamentals and Reasoning Patterns | - AI agent core concepts and architectures - Agent reasoning patterns and workflows |
| Topic 4: Oracle AI Database for Agentic AI | - Oracle AI Vector Search - Agentic AI capabilities in Oracle AI Database |
| Topic 5: Building Agents with LangChain and OpenAI Agent Stack | - OpenAI Agents SDK usage - LangChain components and chains |
| Topic 6: Implementing Model Context Protocol (MCP) | - MCP fundamentals and integration |
Oracle Agentic AI Foundations Associate Sample Questions:
What is the strategic theme behind agentic AI capabilities in Oracle AI Database?
- A. Removing SQL functionality in favor of REST APIs
- B. Replacing the database with a vector-only system
- C. Bringing AI capabilities natively into the database.
- D. Selling vector products without database integration
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Which standard MCP transport supports remote or network-accessible deployments where multiple clients may connect?
- A. STDIO
- B. Raw TCP sockets
- C. Local Unix pipes only
- D. Streamable HTTP
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Which OCI services are used for observability and auditing of deployed AI agents?
- A. OCI Events, OCI Functions, and OCI Vault
- B. OCI Streaming, OCI Queue, and OCI Email Delivery
- C. OCI Data Catalog, OCI Search, and OCI DNS
- D. OCI Logging, OCI Monitoring, and OCI Audit
Explanation: Only visible for VCEDumps members. You can sign-up / login (it's free).
In the context of MCP, what does the "USB-C for AI" analogy emphasize?
- A. MCP is a standardized interface.
- B. MCP makes AI models physically faster.
- C. MCP is preinstalled on all modern computers.
- D. MCP needs specialized hardware to run.
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Compared with a standalone LLM call, an AI agent architecture commonly adds which capabilities?
- A. Larger transformer layers and faster training
- B. Tool access, memory handling, and iterative execution
- C. Replacement of transformer-based inference entirely
- D. Native GUI rendering and visualization support
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