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Oracle 1z0-1157-26 Exam Syllabus Topics:

SectionObjectives
Topic 1: OCI Enterprise AI Agents- OCI Enterprise AI platform
  • 1. Responses API, tools, memory, and vector stores
    • 2. Building and running AI agents
      • 3. Deployment and scaling
        • 4. Agent development, orchestration, and execution
          • 5. OCI Enterprise AI Agents service
            Topic 2: LangChain for AI Agents- LangChain fundamentals
            • 1. Tools, tool schemas, and tool execution
              • 2. Agent invocation and orchestration flow
                • 3. Building agents with LangChain
                  • 4. LangChain and LangChain Expression Language
                    Topic 3: OpenAI Responses API and Agents SDK- OpenAI agent development
                    • 1. Responses API
                      • 2. Guardrails and tracing
                        • 3. Multi-agent handoffs
                          • 4. OpenAI Agents SDK
                            • 5. Function calling and tools
                              Topic 4: Agentic AI for Oracle AI Database- Oracle AI Database agentic AI capabilities
                              • 1. Oracle AI Database Private Agent Factory
                                • 2. Document chunking, embedding generation, and retrieval
                                  • 3. Select AI
                                    • 4. Oracle AI Vector Search
                                      • 5. Vector data types, embeddings, and similarity search
                                        • 6. Oracle Autonomous AI Database MCP Server
                                          • 7. Grounding agent responses with enterprise data
                                            Topic 5: Introduction to MCP- Model Context Protocol fundamentals
                                            • 1. MCP concepts and architecture
                                              • 2. MCP clients and servers
                                                • 3. Tool discovery and interoperability
                                                  Topic 6: Introduction to AI Agents- AI agent fundamentals and architecture
                                                  • 1. AI agents, traditional chatbots, and rule-based systems
                                                    • 2. Agent reasoning patterns including Chain-of-Thought and ReAct
                                                      • 3. Core agent components: LLMs, tools, and orchestration loops
                                                        • 4. Safety, guardrails, and responsible agentic workflows
                                                          - Agent development concepts
                                                          • 1. OpenAI Agents SDK guardrails
                                                            • 2. Function calling and tool use
                                                              • 3. Multi-agent design patterns and handoffs

                                                                Oracle Agentic AI Foundations Associate Sample Questions:

                                                                Question 1

                                                                Which SQL function computes distance between vectors in Oracle AI Vector Search?

                                                                A. VECTOR_DISTANCE()
                                                                B. VECTOR_SCORE()
                                                                C. SCORE_SIMILARITY()
                                                                D. EMBEDDING_DISTANCE()


                                                                Question 2

                                                                Which native column type does Oracle AI Database use for storing vector embeddings?

                                                                A. VECTOR
                                                                B. BLOB
                                                                C. JSON
                                                                D. VARCHAR2


                                                                Question 3

                                                                What is short-term memory compaction in OCI Enterprise AI Agents?

                                                                A. A runtime optimization for Python tools
                                                                B. A masking process for prompt content
                                                                C. A network optimization for agent requests
                                                                D. A summarization process for long conversations


                                                                Question 4

                                                                Which statement describes use cases for input guardrails in the OpenAI Agents SDK?

                                                                A. Checking that the agent's final response meets quality and safety thresholds.
                                                                B. Logging all user inputs to an audit trail for compliance reporting.
                                                                C. Filtering which tools the agent is allowed to call based on user role.
                                                                D. Validating input, detecting unsafe content, and blocking prompt-injection attempts.


                                                                Question 5

                                                                Which approaches are supported by OCI Enterprise AI Agents?

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


                                                                Solutions:

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

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