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Oracle 1z0-1157-26 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| OCI Enterprise AI Agents | 25% | - OCI Enterprise AI platform and agent services
|
| Introduction to AI Agents | 15% | - AI agent fundamentals
|
| Agentic AI for Oracle AI Database | 25% | - Oracle AI Database agentic AI capabilities
|
| Model Context Protocol (MCP) Fundamentals | 15% | - MCP architecture and integration
|
| OpenAI Responses API and Agents SDK | 15% | - OpenAI agent stack
|
| LangChain for AI Agents | 5% | - LangChain fundamentals and agent construction
|
Oracle Agentic AI Foundations Associate Sample Questions:
Question 1
What is the architectural advantage of Autonomous AI Database MCP Server over a separately deployed third- party MCP server?
A. It eliminates the need for SQL queries entirely.
B. It reduces operational overhead and enforces security inside the database.
C. It uses a common MCP host for all database connections.
D. It moves all query execution to a separate compute tier outside the database.
Question 2
What occurs during the MCP initialization phase?
A. The client completes user authentication as part of the protocol initialization exchange.
B. The server executes all tools once to warm internal caches.
C. The LLM is fine-tuned using the server's tool definitions.
D. The client and server exchange protocol versions and supported capabilities.
Question 3
Which statement describes the STDIO transport in MCP?
A. STDIO transport requires OAuth authentication for all requests
B. STDIO transport serializes messages as plain text rather than JSON
C. The host launches the server as a local subprocess communicating via stdin and stdout
D. The server runs as an HTTP service intended for remote multi-client deployments
Question 4
Which approaches can generate embeddings for Oracle AI Vector Search workflows?
A. Export data to a Python environment, generate embeddings, then reimport via SQL Loader
B. Use ONNX models in-database or external REST-based embedding providers
C. Train a custom embedding model and manually insert vectors row by row
D. Use external REST APIs exclusively, since in-database embedding is not supported
Question 5
What is the purpose of OCI Enterprise AI Governance?
A. Applying guardrails, identity controls, and network security controls to AI workloads.
B. Monitoring model latency and optimizing inference throughput.
C. Managing model versions and rolling back failed deployments.
D. Replacing the AI agent runtime layer.
Solutions:
| Question 1 Answer: B | Question 2 Answer: D | Question 3 Answer: C | Question 4 Answer: B | Question 5 Answer: A |





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