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Microsoft GH-300 Exam Overview:
| Certification Vendor: | Microsoft |
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| Exam Name: | GitHub Copilot |
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| Exam Number: | GH-300 |
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| Exam Duration: | 100 minutes |
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| Certificate Validity Period: | 1 year |
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| Exam Price: | $99 USD |
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| Passing Score: | 700 / 1000 |
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| Exam Format: | Multiple-choice, Scenario-based, Proctored |
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| Real Exam Qty: | 60–65 |
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| Available Languages: | French, Portuguese (Brazil), English, Arabic (Saudi Arabia), Chinese (Simplified), German, Korean, Japanese, Spanish |
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| Recommended Training: | Microsoft Learn: GitHub Copilot Learning Path |
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| Exam Registration: | Pearson VUE Registration Microsoft Learn Exam Details |
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| Sample Questions: | Microsoft GH-300 Sample Questions |
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| Exam Way: | Online proctored or onsite at Pearson VUE test centers |
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| Pre Condition: | Basic familiarity with GitHub, software development workflows, and at least one programming language; no formal prerequisites required |
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| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/GH-300 |
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Microsoft GH-300 考試大綱:
| 主題 | 簡介 |
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| 主題 1 | - Domain 6: Testing with GitHub Copilot: This section measures abilities of QA Engineers and Test Automation Specialists to use Copilot for test generation, including unit and integration tests. It explains how Copilot can identify edge cases and assist in writing assertions. The domain also covers different Copilot subscription SKUs, privacy considerations, organizational code suggestion settings, and configuration files related to Copilot.
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| 主題 2 | - GitHub Copilot Plans and Feature: This domain targets Product Managers and DevOps Engineers and focuses on understanding the various GitHub Copilot subscription plans like Individual, Business, and Enterprise, including distinctions and management features. It covers how Copilot is integrated into IDEs, different triggering methods for code suggestions, organizational policy management, subscription administration via API, and effective use of Copilot Chat and Knowledge Bases. Candidates also learn about CLI usage and configuration.
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| 主題 3 | - How GitHub Copilot Works and Handles Data: Designed for Machine Learning Engineers and Data Privacy Specialists, this section covers the data lifecycle and processing behind Copilot’s code suggestions. It explains how context is gathered, prompts constructed, responses generated, and post-processed through proxy services. Candidates understand Copilot’s data policies, handling of inputs, and limitations such as context window size and data age influencing suggestion relevance.
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最新的 GitHub Administrator GH-300 免費考試真題 (Q111-Q116):
問題 #111
What do you check when GitHub Copilot content exclusions are not working? (Each correct answer presents part of the solution. Choose two.)
- A. If GitHub Copilot can connect to the server selected in your user settings.
- B. If the user is part of the content exclusion team that limits the use of content exclusions.
- C. If the user is in an organization that has content exclusions configured.
- D. If the content exclusion settings changed in the last 30 minutes or before that.
答案:C,D
解題說明:
Exact extracts:
* "Changes to content exclusion settings can take up to 30 minutes to take effect." References: GitHub Copilot troubleshooting and content exclusions documentation.
問題 #112
What is used by GitHub Copilot in the IDE to determine the prompt context?
- A. All the code visible in the current IDE.
- B. All the code in the current repository and any git submodules.
- C. Information from the IDE like open tabs, cursor location, selected code.
- D. The open tabs in the IDE and the current folder of the terminal.
答案:C
解題說明:
"GitHub Copilot generates suggestions based on context from the IDE, including the file you are editing, open tabs, cursor position, and any selected code." This proves that the context is drawn from editor state information, making option A correct.
References: GitHub Copilot context and suggestions documentation.
問題 #113
What is the process behind identifying public code matches when using a public code filter enabled in GitHub Copilot?
- A. Analyzing the context and structure of the code being written
- B. Running code suggestions through filters designed to detect public code
- C. Comparing suggestions against public code using machine learning.
- D. Reviewing the user's browsing history to identify public repositories
答案:B
解題說明:
When the public code filter is enabled, GitHub Copilot runs code suggestions through filters designed to detect matches with publicly available code. This helps prevent the generation of code that might infringe on copyright or licensing agreements.
問題 #114
What is the main purpose of the duplication detection filter in GitHub Copilot?
- A. To encourage the user to follow coding best practices preventing code duplication.
- B. To compare user-generated code against a private repository for potential matches.
- C. To detect and block suggestions that match public code snippets on GitHub if they contain about 150 characters.
- D. To allow administrators to control which suggestions are visible to developers based on custom criteria.
答案:C
問題 #115
What are the potential limitations of GitHub Copilot in maintaining existing codebases?
- A. GitHub Copilot can independently manage and resolve all merge conflicts in version control.
- B. GitHub Copilot can refactor and optimize the entire codebase up to 10,000 lines of code.
- C. GitHub Copilot's suggestions are always aware of the entire codebase.
- D. GitHub Copilot might not fully understand the context and dependencies within a large codebase.
答案:D
解題說明:
"Copilot may not always understand the full context or complex dependencies in large codebases, and suggestions may require significant review." This proves that the main limitation is a lack of deep awareness of complex or large codebase contexts.
References: GitHub Copilot limitations documentation.
問題 #116
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