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Oracle Cloud Infrastructure Enterprise AI Professional (1Z0-1158-26) Syllabus

Applying Large Language Model Concepts

Explaining how large language models work and how prompting and customization shape their output.

10%
Weight
5
Questions
10
Marks

LLM Architecture and Behavior

  • Transformer and decoder-only model basics
  • Tokens, context windows and embeddings
  • Decoding settings: temperature, top-p, top-k
  • Hallucination and grounding

Prompting and Customization

  • Prompt engineering and in-context learning
  • Retrieval-augmented generation concepts
  • Fine-tuning vs. prompting trade-offs
  • Choosing a customization approach

Applying Agentic AI Concepts

Applying agent design concepts such as reasoning patterns, tool use, memory and multi-agent orchestration.

20%
Weight
10
Questions
20
Marks

Agent Fundamentals

  • Agents vs. chat applications
  • Reasoning patterns such as ReAct and planning
  • Tool and function calling
  • Short-term and long-term memory

Agent Protocols and Orchestration

  • Model Context Protocol (MCP) tools
  • Agent-to-agent communication patterns
  • Multi-agent orchestration
  • Human-in-the-loop checkpoints

Configuring OCI Enterprise AI Models

Selecting, customizing and serving models in OCI Enterprise AI.

20%
Weight
10
Questions
20
Marks

Model Selection and Access

  • Pretrained chat and embedding models on OCI
  • On-demand vs. dedicated AI clusters
  • OpenAI-compatible OCI Responses API
  • Model endpoints and parameters

Model Customization

  • Fine-tuning methods such as LoRA and T-Few
  • Preparing training data
  • Hosting custom models on dedicated clusters
  • Evaluating fine-tuned models

Building OCI Enterprise AI Agents

Building agents on OCI with the Responses API, tools and retrieval.

25%
Weight
13
Questions
25
Marks

Agents with the Responses API

  • Agent loops with the Responses API
  • Defining function tools
  • Built-in tools and code execution
  • Conversation state management

Retrieval and Tool Integration

  • RAG with vector stores and knowledge bases
  • SQL and database tools
  • MCP server integration
  • Error handling and retries for tools

Building and Deploying Hosted Agents

Packaging and deploying agents as hosted deployments on OCI.

15%
Weight
7
Questions
15
Marks

Hosted Agent Deployments

  • Hosted agent application packaging
  • Deployment configuration and scaling
  • Endpoints and authentication
  • Versioning and updates

Integration and Operations

  • Connecting hosted agents to applications
  • IAM policies and compartments
  • Logging and monitoring deployments
  • Troubleshooting deployments

Governing and Optimizing OCI Enterprise AI

Applying guardrails, observability and cost controls to production AI workloads.

10%
Weight
5
Questions
10
Marks

Guardrails and Responsible AI

  • Content moderation guardrails
  • Prompt injection protection
  • PII detection and handling
  • Data privacy and security on OCI

Observability and Cost

  • Tracing and evaluating agent runs
  • Usage metrics and monitoring
  • Cost optimization choices
  • Quotas and limits

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Learning Progress

Applying Large Language Model Concepts 85%
Applying Agentic AI Concepts 92%

Practice Test Scores

95%
Latest Score
Above passing threshold

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