Agentic AI Foundations Associate: 1z0-1157-26 Exam


"Agentic AI Foundations Associate", also known as 1z0-1157-26 exam, is a Oracle Certification. With the complete collection of questions and answers, PrepAwayTest has assembled to take you through 60 Q&As to your 1z0-1157-26 Exam preparation. In the 1z0-1157-26 exam resources, you will cover every field and category in Oracle Certification Certification helping to ready you for your successful Oracle Certification.

  • Exam Code: 1z0-1157-26
  • Exam Name: Agentic AI Foundations Associate
  • Total Questions: 60

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Oracle 1z0-1157-26 Exam Syllabus Topics:

SectionWeightObjectives
Agentic AI for Oracle AI Database25%- Oracle AI Database agentic AI capabilities
  • 1. Oracle AI Vector Search workflow: document chunking, embedding generation, similarity search, and retrieval
    • 2. Select AI for natural-language interaction with Oracle AI Database
      • 3. Oracle AI Database Private Agent Factory
        • 4. Grounding agent responses with enterprise data from Oracle AI Database
          • 5. VECTOR data type, vector embeddings, and similarity search
            • 6. Oracle AI Vector Search, Select AI, and MCP integration
              • 7. Oracle Autonomous AI Database MCP Server
                OpenAI Responses API and Agents SDK15%- OpenAI agent stack
                • 1. Function calling and tools
                  • 2. OpenAI Responses API for agentic applications
                    • 3. Agents SDK primitives: Agent, Runner, Tool, Handoffs, and Guardrails
                      • 4. Multi-agent design patterns and handoffs
                        • 5. Guardrails for validating inputs, outputs, and agent actions
                          Introduction to AI Agents15%- AI agent fundamentals
                          • 1. Safety considerations and guardrail techniques
                            • 2. Core components of an AI agent: LLM, tools, and orchestration loop
                              • 3. Agent reasoning patterns: Chain-of-Thought and ReAct
                                • 4. Differentiate AI agents from traditional chatbots and rule-based workflows
                                  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
                                        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. MCP hosts, clients, servers, tools, resources, and prompts
                                                • 5. Integrating MCP capabilities into agentic AI workflows
                                                  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 Agents development, orchestration, and execution
                                                      • 3. OCI Enterprise AI platform services for the enterprise AI agent lifecycle
                                                        • 4. OCI Enterprise AI Agents building blocks: Responses API, tools, memory, and vector stores
                                                          • 5. Deployment and scaling options

                                                            Oracle Agentic AI Foundations Associate Sample Questions:

                                                            What is the default distance metric for VECTOR_DISTANCE in Oracle for non-BINARY vectors?

                                                            • A. Euclidean (L2) distance
                                                            • B. Bitwise XOR distance
                                                            • C. COSINE distance
                                                            • D. Levenshtein edit distance
                                                            Reveal Solution  Discussion  0

                                                            Correct Answer: C  🗳️

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

                                                            Assume an agent has access to the tools multiply(a, b) and divide(a, b). A user asks: "What is 15 multiplied by
                                                            8, then divided by 3?" In the OpenAI Agents SDK, how does the agent loop handle this multi-step task?

                                                            • A. The model calls multiply(15, 8), receives the result, then calls divide(120, 3)
                                                            • B. The model calls every available arithmetic tool before answering
                                                            • C. The Runner performs all arithmetic internally without involving the model or tools
                                                            • D. The SDK automatically combines all arithmetic operations into a single tool call
                                                            Reveal Solution  Discussion  0

                                                            Correct Answer: A  🗳️

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

                                                            Which prompt addition is used for zero-shot Chain-of-Thought prompting?

                                                            • A. Let's think step by step.
                                                            • B. Disable all external retrieval tools.
                                                            • C. Set temperature equal to zero.
                                                            • D. Upload a structured CSV first.
                                                            Reveal Solution  Discussion  0

                                                            Correct Answer: A  🗳️

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

                                                            How are tool calls handled between the LLM and the application?

                                                            • A. It performs the external operation directly during inference.
                                                            • B. It grants the orchestration layer unrestricted system access.
                                                            • C. It generates a tool-call request for the application to validate and run.
                                                            • D. It allows tools to run without application control.
                                                            Reveal Solution  Discussion  0

                                                            Correct Answer: C  🗳️

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

                                                            Which authentication approach should be used for production-grade access to OCI Enterprise AI services?

                                                            • A. Browser session cookies stored with application code
                                                            • B. Anonymous access to tenancy-level resources
                                                            • C. Hardcoded credentials checked into source repositories
                                                            • D. OCI IAM authentication with signed requests and IAM policies
                                                            Reveal Solution  Discussion  0

                                                            Correct Answer: D  🗳️

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

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