GH-600トレーニング & GH-600試験復習赤本

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Microsoft GH-600 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Implement agents and multi-agent systems30%- Build agents with Azure AI tools and frameworks
  • 1. Develop using Semantic Kernel and Azure AI Foundry
    • 2. Integrate models and prompts
      • 3. Implement agent logic and reasoning
        - Orchestrate multi-agent collaboration
        • 1. Manage agent handoffs and task distribution
          • 2. Define communication protocols between agents
            • 3. Implement workflows and coordination strategies
              Topic 2: Test, deploy, and monitor agentic AI systems20%- Validate agent performance and safety
              • 1. Test reasoning accuracy and consistency
                • 2. Evaluate quality metrics and iterate
                  • 3. Apply guardrails and content safety
                    - Deploy and monitor agents at scale
                    • 1. Implement logging, telemetry, and observability
                      • 2. Deploy to Azure AI and cloud environments
                        • 3. Optimize cost, latency, and throughput
                          Topic 3: Integrate tools, data, and services25%- Connect data sources and knowledge bases
                          • 1. Integrate vector databases and search
                            • 2. Implement retrieval-augmented generation (RAG)
                              • 3. Ensure data security and access control
                                - Incorporate external tools and APIs
                                • 1. Implement function calling and service integration
                                  • 2. Design and register tool definitions
                                    • 3. Handle authentication and error resilience
                                      Topic 4: Design agentic AI solutions25%- Define requirements for agentic systems
                                      • 1. Identify use cases and scenarios
                                        • 2. Define functional and non-functional requirements
                                          • 3. Plan for responsible AI and governance
                                            - Design agent architecture
                                            • 1. Plan tool integration and orchestration
                                              • 2. Select agent patterns and topologies
                                                • 3. Design memory and state management

                                                  >> GH-600トレーニング <<

                                                  権威のあるGH-600トレーニングと実際的なGH-600試験復習赤本

                                                  試験を受けることでMicrosoft認定を取得することを期待する人が増えています。ただし、多くの人にとって試験は非常に困難です。特に正しい学習教材を選択せず​​に適切な方法を見つけた場合、GH-600試験に合格して関連する認定を取得することはより困難になります。関連する認定を効率的な方法で取得したい場合は、当社のGH-600学習教材を選択してください。弊社のGH-600学習教材が試験に合格し、簡単に認定を取得するのに役立ちます。

                                                  Microsoft Developing in Agentic AI Systems 認定 GH-600 試験問題 (Q29-Q34):

                                                  質問 # 29
                                                  In Microsoft Visual Studio Code, you are using GitHub Copilot Chat to generate documentation for a new feature.
                                                  Earlier in the day, you used Copilot Chat extensively for an unrelated refactoring task.
                                                  You discover that the Copilot responses for the new documentation task are influenced by the earlier conversation.
                                                  You need Copilot to focus only on the current task and avoid using prior conversational context. The solution must NOT affect other conversations.
                                                  What should you do?

                                                  正解：A

                                                  解説：
                                                  Starting a new Copilot Chat conversation establishes a separate conversational context for the documentation task. The unrelated refactoring exchanges remain in their original conversation instead of continuing to influence the new thread. This directly addresses the requirement to separate tasks while preserving other conversations.
                                                  Conversation history contributes information beyond the latest prompt. Earlier instructions, assumptions, terminology, and design decisions can continue to affect subsequent responses within the same session. A fresh conversation provides a clear task boundary, allowing the developer to supply the feature requirements and relevant documentation context explicitly.
                                                  Changing from sidebar chat to inline chat changes the interaction surface; it does not provide the same explicit separation of conversational history. Referencing a file supplies relevant context but does not reliably remove earlier instructions. The maximum requests setting governs agent execution limits rather than conversation isolation. Clearing history is also unnecessary when the previous work can remain available in its own session.
                                                  A new conversation can still receive applicable repository instructions and deliberately supplied context; it is the previous conversation that is separated.
                                                  Study-guide topics: conversational state, context isolation, and task boundaries. Reference: VS Code-Manage agent sessions.


                                                  質問 # 30
                                                  You have a GitHub repository.
                                                  You use the GitHub Copilot CLI to run an agentic workflow from the terminal.
                                                  During execution, the conversation history approaches the context limit. The agent cannot continue the current session unless the amount of retained context is reduced.
                                                  You need to continue the current session without losing all prior progress.
                                                  Which Copilot CLI slash command should you run?

                                                  正解：B

                                                  解説：
                                                  The /compact command reduces the active conversation context while preserving a condensed summary of the important work completed so far. It is designed for long-running agent sessions that approach the context-window limit.
                                                  /clear would remove the session context rather than preserve the useful implementation history. This creates a sharper loss of continuity and does not meet the requirement to retain prior progress. /yolo concerns approval behavior, not context reduction. /context is used to inspect or manage context information but does not perform the required compaction.
                                                  Compaction is most effective when durable project state already exists in repository artifacts: source changes, commits, task files, plans, and test outputs. The summarized context can then retain decisions and current goals while the repository continues to hold the detailed implementation record.
                                                  Study-guide topics: context compaction, long-running sessions, durable state, and execution continuity.


                                                  質問 # 31
                                                  You have a GitHub repository that contains an agent named Orchestrator.Orchestrator delegates work to the following specialized subagents:
                                                  - Planner reviews issues and creates a plan of action.
                                                  - Implementer writes code based on the plan of action.
                                                  - Reviewer reviews the code.
                                                  You create a new agent named Summarizer that produces a concise summary of the work performed by the other agents.
                                                  You need to ensure that Orchestrator can invoke Summarizer as part of its workflow.
                                                  What should you do?

                                                  正解：D

                                                  解説：
                                                  To ensure that Orchestrator can invoke the new Summarizer agent as part of its workflow, you should take the following action: In the YAML frontmatter of the Orchestrator agent, add Summarizer to the agents list.
                                                  In GitHub Copilot custom agent configurations (defined in .agent.md files), the properties specified in the YAML frontmatter serve distinct purposes:
                                                  agents: This field acts as an explicit whitelist of other custom subagents that the parent agent is allowed to invoke and delegate work to. Adding Summarizer here registers it as an authorized subagent within the Orchestrator workflow.
                                                  Reference:
                                                  https://awesome-copilot.github.com/learning-hub/building-custom-agents/


                                                  質問 # 32
                                                  You want the GitHub Copilot coding agent to follow project-specific conventions (coding style, testing requirements, folder structure) on every task it performs in a repository. What should you create?

                                                  正解：C

                                                  解説：
                                                  Placing a copilot-instructions.md file inside the .github/ folder lets you define repository-wide custom instructions that Copilot automatically applies to every chat and agent session, ensuring consistent adherence to conventions without repeating them in every prompt.


                                                  質問 # 33
                                                  You have a GitHub Enterprise Cloud repository that uses the GitHub Copilot coding agent to resolve backlog issues by creating draft pull requests. The repository uses a GitHub Actions workflow for deployments to the production environment.
                                                  You discover that the workflow is being triggered before human review.
                                                  You need to configure GitHub controls to meet the following requirements:
                                                  The workflow for the agent's draft pull requests must NOT run until a user that has write access approves the pull requests.
                                                  Production deployment jobs must start only after a user with write access explicitly approves the jobs.
                                                  Which controls should you configure? To answer, drag the appropriate controls to the correct requirements.

                                                  正解：

                                                  解説：


                                                  質問 # 34
                                                  ......

                                                  GH-600試験に合格することが、最高のキャリアの機会です。 関連する証明書の豊富な経験は、企業があなたの選択のために一連の専門的な空席を開くために重要です。 当社のウェブサイトのGH-600学習クイズバンクおよび教材は、選択したトピックに基づいて最新の質問と回答を検索します。 この選択は、あなたのキャリア全体の突破口となるので、GH-600スタディガイドの高い品質と正確性に驚かされるでしょう。

                                                  GH-600試験復習赤本: https://www.pass4test.jp/GH-600.html