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Oracle 1z0-1157-26 Exam Syllabus Topics:

SectionWeightObjectives
Introduction to AI Agents15%- AI agent fundamentals
  • 1. Differentiate AI agents from traditional chatbots and rule-based workflows
    • 2. Core components of an AI agent: LLM, tools, and orchestration loop
      • 3. Agent reasoning patterns: Chain-of-Thought and ReAct
        • 4. Safety considerations and guardrail techniques
          Agentic AI for Oracle AI Database25%- Oracle AI Database agentic AI capabilities
          • 1. Select AI for natural-language interaction with Oracle AI Database
            • 2. Grounding agent responses with enterprise data from Oracle AI Database
              • 3. Oracle AI Vector Search workflow: document chunking, embedding generation, similarity search, and retrieval
                • 4. Oracle AI Database Private Agent Factory
                  • 5. Oracle Autonomous AI Database MCP Server
                    • 6. VECTOR data type, vector embeddings, and similarity search
                      • 7. Oracle AI Vector Search, Select AI, and MCP integration
                        OpenAI Responses API and Agents SDK15%- OpenAI agent stack
                        • 1. OpenAI Responses API for agentic applications
                          • 2. Function calling and tools
                            • 3. Agents SDK primitives: Agent, Runner, Tool, Handoffs, and Guardrails
                              • 4. Guardrails for validating inputs, outputs, and agent actions
                                • 5. Multi-agent design patterns and handoffs
                                  Model Context Protocol (MCP) Fundamentals15%- MCP architecture and integration
                                  • 1. MCP transport options including stdio and Streamable HTTP
                                    • 2. JSON-RPC 2.0 message format
                                      • 3. Role of MCP in standardizing integration between AI agents and external tools
                                        • 4. Integrating MCP capabilities into agentic AI workflows
                                          • 5. MCP hosts, clients, servers, tools, resources, and prompts
                                            OCI Enterprise AI Agents25%- OCI Enterprise AI platform and agent services
                                            • 1. Building and running AI agents with OCI Enterprise AI Agents
                                              • 2. OCI Enterprise AI platform services for the enterprise AI agent lifecycle
                                                • 3. OCI Enterprise AI Agents development, orchestration, and execution
                                                  • 4. Deployment and scaling options
                                                    • 5. OCI Enterprise AI Agents building blocks: Responses API, tools, memory, and vector stores
                                                      LangChain for AI Agents5%- LangChain fundamentals and agent construction
                                                      • 1. LangChain agent reasoning and tool execution flow
                                                        • 2. LangChain core abstractions: chat models, prompts, tools, and agents
                                                          • 3. LangChain tools, prompts, and chains

                                                            Oracle Agentic AI Foundations Associate Sample Questions:

                                                            Compared with a standalone LLM call, an AI agent architecture commonly adds which capabilities?

                                                            • A. Native GUI rendering and visualization support
                                                            • B. Larger transformer layers and faster training
                                                            • C. Replacement of transformer-based inference entirely
                                                            • D. Tool access, memory handling, and iterative execution
                                                            Answer: D

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                                                            Which OCI services are used for observability and auditing of deployed AI agents?

                                                            • A. OCI Data Catalog, OCI Search, and OCI DNS
                                                            • B. OCI Logging, OCI Monitoring, and OCI Audit
                                                            • C. OCI Events, OCI Functions, and OCI Vault
                                                            • D. OCI Streaming, OCI Queue, and OCI Email Delivery
                                                            Answer: B

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                                                            In the OpenAI Agents SDK, how does a Handoff differ from the Manager pattern?

                                                            • A. A Handoff transfers control; a Manager keeps control.
                                                            • B. A Handoff uses async execution; a Manager uses sync execution.
                                                            • C. A Handoff keeps control; a Manager transfers control.
                                                            • D. A Handoff calls tools directly; a Manager only routes messages.
                                                            Answer: A

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                                                            In the OpenAI Agents SDK, what is the role of the Runner?

                                                            • A. It handles authentication and rotates API keys for the agent.
                                                            • B. It is the deployment platform for hosting agents in production.
                                                            • C. It executes the agent loop.
                                                            • D. It defines JSON schemas for function tools at compile time.
                                                            Answer: C

                                                            Explanation: Only visible for PassLeaderVCE members. You can sign-up / login (it's free).

                                                            Which message format does MCP use for client-server communication?

                                                            • A. GraphQL
                                                            • B. SOAP/XML
                                                            • C. Protocol Buffers
                                                            • D. JSON-RPC 2.0
                                                            Answer: D

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