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Oracle 1z0-1157-26 Exam Overview:

Certification Vendor:Oracle
Exam Name:Agentic AI Foundations Associate
Exam Number:1Z0-1157-26
Available Languages:Japanese, English
Exam Duration:60 minutes
Certificate Validity Period:Oracle Foundations certifications do not have a stated expiration period
Passing Score:65%
Exam Format:Multiple-choice questions
Exam Price:Free
Related Certifications:Agentic AI Certified Foundations Associate
Real Exam Qty:40
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 Autonomous AI Database MCP Server
    • 2. Oracle AI Vector Search workflow: document chunking, embedding generation, similarity search, and retrieval
      • 3. Oracle AI Database Private Agent Factory
        • 4. VECTOR data type, vector embeddings, and similarity search
          • 5. Grounding agent responses with enterprise data from Oracle AI Database
            • 6. Select AI for natural-language interaction with Oracle AI Database
              • 7. Oracle AI Vector Search, Select AI, and MCP integration
                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
                      Introduction to AI Agents15%- AI agent fundamentals
                      • 1. Agent reasoning patterns: Chain-of-Thought and ReAct
                        • 2. Core components of an AI agent: LLM, tools, and orchestration loop
                          • 3. Differentiate AI agents from traditional chatbots and rule-based workflows
                            • 4. Safety considerations and guardrail techniques
                              Model Context Protocol (MCP) Fundamentals15%- MCP architecture and integration
                              • 1. MCP transport options including stdio and Streamable HTTP
                                • 2. Role of MCP in standardizing integration between AI agents and external tools
                                  • 3. Integrating MCP capabilities into agentic AI workflows
                                    • 4. JSON-RPC 2.0 message format
                                      • 5. MCP hosts, clients, servers, tools, resources, and prompts
                                        OCI Enterprise AI Agents25%- OCI Enterprise AI platform and agent services
                                        • 1. OCI Enterprise AI Agents building blocks: Responses API, tools, memory, and vector stores
                                          • 2. OCI Enterprise AI Agents development, orchestration, and execution
                                            • 3. Deployment and scaling options
                                              • 4. OCI Enterprise AI platform services for the enterprise AI agent lifecycle
                                                • 5. Building and running AI agents with OCI Enterprise AI Agents
                                                  OpenAI Responses API and Agents SDK15%- OpenAI agent stack
                                                  • 1. Multi-agent design patterns and handoffs
                                                    • 2. Function calling and tools
                                                      • 3. OpenAI Responses API for agentic applications
                                                        • 4. Guardrails for validating inputs, outputs, and agent actions
                                                          • 5. Agents SDK primitives: Agent, Runner, Tool, Handoffs, and Guardrails

                                                            Oracle Agentic AI Foundations Associate Sample Questions:

                                                            Question 1

                                                            Which approaches are supported by OCI Enterprise AI Agents?

                                                            A. Build a frontend agent or a backend agent.
                                                            B. Deploy using Python-only or Java-only options.
                                                            C. Call the Responses API directly or deploy a hosted agent application.
                                                            D. Select a free or paid deployment model.


                                                            Question 2

                                                            In the given LangChain chain, what is the role of StrOutputParser()? chain = prompt

                                                            A. It extracts plain text from the model response.
                                                            B. It sends the prompt to the model API.
                                                            C. It stores tool execution history.
                                                            D. StrOutputParser()


                                                            Question 3

                                                            When is MCP most valuable?

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


                                                            Question 4

                                                            Which MCP primitive is model-controlled and used to perform actions?

                                                            A. Schemas
                                                            B. Prompts
                                                            C. Tools
                                                            D. Resources


                                                            Question 5

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

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


                                                            Solutions:

                                                            Question 1
                                                            Answer: C
                                                            Question 2
                                                            Answer: A
                                                            Question 3
                                                            Answer: B
                                                            Question 4
                                                            Answer: C
                                                            Question 5
                                                            Answer: D

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