Oracle 1Z0-1158-26 Certification Exam Syllabus

1Z0-1158-26 Syllabus, 1Z0-1158-26 Latest Dumps PDF, Oracle Cloud Infrastructure Enterprise AI Professional Dumps, 1Z0-1158-26 Free Download PDF Dumps, Cloud Infrastructure Enterprise AI Professional DumpsYou can use this Oracle 1Z0-1158-26 exam study guide to collect all the information about the Oracle Cloud Infrastructure Enterprise AI Professional exam. The Oracle 1Z0-1158-26 certification exam is mainly targeted to those candidates who have some experience or exposure to Oracle Cloud Infrastructure technology and want to flourish their career with Oracle Cloud Infrastructure Certified Enterprise AI Professional credential.

The Oracle 1Z0-1158-26 certification exam validates your understanding of the Oracle Cloud Infrastructure technology and sets the stage for your future progression. Your preparation plan for Oracle Cloud Infrastructure Enterprise AI Professional Certification exam should include hands-on practice or on-the-job experience performing the tasks described in following certification exam syllabus topics.

Oracle 1Z0-1158-26 Exam Details:

Exam Name Oracle Cloud Infrastructure Enterprise AI Professional
Exam Code 1Z0-1158-26
Exam Price USD $245 (Pricing may vary by country or by localized currency)
Duration 90 minutes
Number of Questions 50
Passing Score 68%
Format Multiple Choice Questions (MCQ)
Recommended Training Become an OCI Enterprise AI Professional
Schedule Exam Buy Oracle Training and Certification
Sample Questions Oracle Cloud Infrastructure Certified Enterprise AI Professional
Recommended Practice 1Z0-1158-26 Online Practice Exam

Oracle 1Z0-1158-26 Syllabus Topics:

Applying Large Language Model Concepts - Explain how LLMs use tokenization and text generation mechanisms to process inputs and generate outputs.
- Evaluate encoder-only, decoder-only, and encoder-decoder LLM architectures to select the appropriate architecture for specified use cases.
- Design and refine advanced prompts to improve LLM performance for complex, domain-specific tasks.
- Compare LLM fine-tuning techniques to determine the appropriate customization approach for a given requirement.
- Explain the capabilities and use cases of code models, multimodal models, and language agents.		 10%
Applying Agentic AI Concepts - Differentiate AI agents from traditional chatbots and workflows based on autonomy, reasoning, and tool use.
- Analyze the agent loop and the perceive-reason-act-observe cycle to determine how agents make decisions and complete tasks.
- Determine how tools extend agent capabilities and select appropriate tool categories for common agent tasks.
- Explain how MCP standardizes connections between agents, tools, and external data sources.
- Compare short-term and long-term memory in agentic systems and determine when each is used.
- Build a working agent by applying the Responses API to implement reasoning, tool use, and response generation.		 20%
Configuring OCI Enterprise AI Models  -Evaluate OCI Enterprise AI model capabilities to determine how the service supports enterprise AI workloads.
- Classify OCI Enterprise AI pretrained foundation model families based on their capabilities and intended use cases.
- Compare approaches for customizing LLMs with enterprise data to meet specific business requirements.
- Configure fine-tuning and inference workflows in OCI Enterprise AI by selecting appropriate hyperparameters.
- Determine dedicated AI cluster sizing, unit shapes, pricing options, and endpoint configuration requirements.		 20%
Building OCI Enterprise AI Agents - Explain how OCI Enterprise AI Agents supports agent development, orchestration, and execution.
- Analyze the OCI Responses API design for OpenAI compatibility by examining its modular primitives and execution flow.
- Select built-in OCI Responses API tools, including Code Interpreter, File Search, MCP Calling, and Function tools, for specified agent tasks.
- Explain the role of MCP in OCI Enterprise AI and how Remote MCP Calling enables agent-tool connectivity.
- Compare short-term memory, long-term memory, and short-term memory compaction in OCI Agent Memory.
- Apply the OCI Vector Stores API and Files API to ground agent responses in relevant enterprise content.		 25%
Building and Deploying Hosted Agents - Explain how hosted agents in OCI Enterprise AI Applications provide a managed runtime for containerized agent workloads.
- Deploy an agent by packaging it as a container image and applying the OCI hosted agent deployment workflow.		 15%
Governing and Optimizing OCI Enterprise AI - Configure secure access controls for OCI Enterprise AI resources according to enterprise security requirements.
- Explain how OCI Enterprise AI protects customer data at rest and in transit.
- Apply guardrails for content moderation, prompt injection defense, and personally identifiable information handling.
- Implement observability and cost management practices to monitor OCI Enterprise AI agents and optimize operational efficiency.		 10%

The Oracle Cloud Infrastructure Enterprise AI Professional Certification Program certifies candidates on skills and knowledge related to Oracle Cloud Infrastructure products and technologies. The Oracle 1Z0-1158-26 is granted based on a combination of passing exams, training, and performance-based assignments, depending on the level of certification. Oracle Cloud Infrastructure Enterprise AI Professional certification is a real benchmark of experience and expertise that helps you stand out in a crowd among employers. To ensure success, Oracle recommends combining education courses, practice exams, and hands-on experience to prepare for your Oracle Cloud Infrastructure Certified Enterprise AI Professional certification exam as questions will test your ability to apply the knowledge you have gained in hands-on practice or professional experience.

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