Prepare with Oracle 1z0-1157-26 exam practice material, pass for sure

Updated: Sep 17, 2026

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Oracle 1z0-1157-26 Exam Overview:

Certification Vendor:Oracle
Exam Name:Agentic AI Foundations Associate
Exam Number:1Z0-1157-26
Certificate Validity Period:Oracle Foundations certifications do not have a stated expiration period
Exam Format:Multiple-choice questions
Available Languages:English, Japanese
Exam Price:Free
Real Exam Qty:40
Exam Duration:60 minutes
Related Certifications:Agentic AI Certified Foundations Associate
Passing Score:65%
Recommended Training:Oracle Agentic AI Foundations: Get skilled for the Agentic AI Era
Oracle Agentic AI Foundations Course
Exam Registration:Oracle Certification
Oracle MyLearn - Agentic AI Foundations Associate Learning Path
Sample Questions:Oracle 1z0-1157-26 Sample Questions
Exam Way:Online certification exam delivered through Oracle MyLearn/CertView.
Pre Condition:No prerequisite certification is stated. Oracle recommends basic familiarity with LLM concepts, practical Python knowledge, and basic Oracle Cloud Infrastructure (OCI) knowledge.
Official Syllabus URL:https://www.oracle.com/education/certification/

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. Oracle Autonomous AI Database MCP Server
      • 3. Oracle AI Vector Search, Select AI, and MCP integration
        • 4. Oracle AI Database Private Agent Factory
          • 5. VECTOR data type, vector embeddings, and similarity search
            • 6. Select AI for natural-language interaction with Oracle AI Database
              • 7. Grounding agent responses with enterprise data from Oracle AI Database
                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. Differentiate AI agents from traditional chatbots and rule-based workflows
                              • 3. Agent reasoning patterns: Chain-of-Thought and ReAct
                                • 4. Core components of an AI agent: LLM, tools, and orchestration loop
                                  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. Deployment and scaling options
                                        • 4. OCI Enterprise AI Agents development, orchestration, and execution
                                          • 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 tools, prompts, and chains
                                                • 3. LangChain core abstractions: chat models, prompts, tools, and agents
                                                  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

                                                            Oracle Agentic AI Foundations Associate Sample Questions:

                                                            Question #1

                                                            When is MCP most valuable?

                                                            • A. When building a single-agent app with no external dependencies.
                                                            • B. When defining prompts and output parsers inside a single LangChain chain.
                                                            • C. When tools are external or cloud-hosted.
                                                            • D. For simple local utilities like add() and multiply() .
                                                            Reveal Solution  Discussion  0

                                                            Correct Answer: C  🗳️

                                                            Explanation: Only visible for Test4Sure members. You can sign-up / login (it's free).

                                                            Question #2

                                                            How do On-Demand serving and Dedicated AI Clusters differ for OCI Enterprise AI Models?

                                                            • A. On-Demand doesn't use processors while Dedicated AI Clusters use isolated GPUs for all workloads.
                                                            • B. On-Demand supports only embedding models while Dedicated AI Clusters support generative models.
                                                            • C. Both options use identical infrastructure but are differentiated by pricing and branding only.
                                                            • D. On-Demand uses shared infrastructure while Dedicated AI Clusters provide isolated GPUs required for custom models.
                                                            Reveal Solution  Discussion  0

                                                            Correct Answer: D  🗳️

                                                            Explanation: Only visible for Test4Sure members. You can sign-up / login (it's free).

                                                            Question #3

                                                            Which statement describes an LLM-based AI agent?

                                                            • A. A chatbot interface with additional visual components.
                                                            • B. A model-based system that uses tools and orchestration.
                                                            • C. A specialized transformer architecture.
                                                            • D. A newly trained standalone model type.
                                                            Reveal Solution  Discussion  0

                                                            Correct Answer: B  🗳️

                                                            Explanation: Only visible for Test4Sure members. You can sign-up / login (it's free).

                                                            Question #4

                                                            What is the purpose of the Vector Stores API?

                                                            • A. Encrypting Object Storage buckets.
                                                            • B. Translating text between languages.
                                                            • C. Streaming video into AI agents.
                                                            • D. Indexing and retrieving data by meaning.
                                                            Reveal Solution  Discussion  0

                                                            Correct Answer: D  🗳️

                                                            Explanation: Only visible for Test4Sure members. You can sign-up / login (it's free).

                                                            Question #5

                                                            Which four behaviors does every Select AI Agent perform?

                                                            • A. Plan, Use tools, Summarize, and Terminate
                                                            • B. Retrieve, Rank, Generate, and Validate
                                                            • C. Plan, Execute, Monitor, and Scale
                                                            • D. Plan, Use tools, Reflect, and Remember
                                                            Reveal Solution  Discussion  0

                                                            Correct Answer: D  🗳️

                                                            Explanation: Only visible for Test4Sure members. You can sign-up / login (it's free).

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