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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 Price: | $99 USD |
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| Real Exam Qty: | 60–65 |
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| Passing Score: | 700 / 1000 |
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| Exam Duration: | 100 minutes |
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| Available Languages: | English, French, Chinese (Simplified), Arabic (Saudi Arabia), German, Korean, Portuguese (Brazil), Japanese, Spanish |
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| Exam Format: | Proctored, Scenario-based, Multiple-choice |
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| Certificate Validity Period: | 1 year |
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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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GitHub Copilot Exam Demo - GH-300 Torrent Vce & GitHub Copilot Pass Guide
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| Topic | Details |
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| Topic 1 | - Developer Use Cases for AI: Targeting Software Engineers and Technical Leads, this domain elaborates on how AI improves developer productivity across common tasks like learning new languages, translation, documentation, debugging, data science, and refactoring. It discusses Copilot’s support in software development lifecycle management and highlights its limitations. Use of the productivity API to track Copilot’s impact is also included.
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| Topic 2 | - Privacy Fundamentals and Context Exclusions: This domain focuses on Security Engineers and Compliance Officers and addresses improving code quality with Copilot’s test suggestions and security optimizations. It covers identification of security vulnerabilities, performance enhancements, and privacy features like content exclusions at repository and organization levels with explanation of their limitations. Candidates learn about safeguarding mechanisms such as duplication detection, contractual protections, security checks, and troubleshooting guide for common Copilot issues including context exclusions and suggestion gaps.
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| Topic 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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| Topic 4 | - 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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| Topic 5 | - Responsible :This section of the exam measures skills of AI Ethics Officers and Risk Managers and covers the responsible and ethical usage of AI technologies. It explains the risks and limitations associated with generative AI tools, including biases in training data and the need to validate AI outputs. Candidates learn how to operate AI responsibly by identifying potential harms such as bias, fairness, privacy concerns, and mitigating these harms by applying ethical AI principles.
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Microsoft GitHub Copilot Sample Questions (Q93-Q98):
NEW QUESTION # 93
How can GitHub Copilot assist developers during the requirements analysis phase of the Software Development Life Cycle (SDLC)?
- A. By managing stakeholder communication and meetings.
- B. By identifying and fixing potential requirement conflicts when using /help.
- C. By automatically generating detailed requirements documents.
- D. By providing templates and code snippets that help in documenting requirements.
Answer: D
Explanation:
GitHub Copilot can assist during the requirements analysis phase by providing templates and code snippets that aid in documenting requirements. This helps streamline the process of capturing and organizing project requirements.
NEW QUESTION # 94
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.
Answer: D
Explanation:
"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.
NEW QUESTION # 95
What is a likely effect of GitHub Copilot being trained on commonly used code patterns?
- A. Suggest code snippets that reflect the most common practices in the training data.
- B. Suggest innovative coding solutions that are not yet popular.
- C. Suggest homogeneous solutions if provided a diverse data set.
- D. Suggest completely novel projects, while reducing time on a project.
Answer: A
Explanation:
GitHub Copilot is likely to suggest code snippets that reflect common practices in its training data, as it learns from frequently used patterns.
NEW QUESTION # 96
What specific function does the /fix slash command perform?
- A. Proposes changes for detected issues, suggesting corrections for syntax errors and programming mistakes.
- B. Generates new code snippets based on language syntax and best practices.
- C. Converts pseudocode into executable code, optimizing for readability and maintainability.
- D. Initiates a code review with static analysis tools for security and logic errors.
Answer: A
Explanation:
"/fix: Propose changes to resolve detected issues, such as syntax errors or common programming mistakes, in the selected code." This confirms that the /fix command is used to suggest corrections for identified problems.
References: GitHub Copilot Chat command reference.
NEW QUESTION # 97
Which of the following prompts can be used to guide GitHub Copilot Chat in refactoring code for quality improvements? (Each correct answer presents part of the solution. Choose two.)
- A. "Refactor my application to meet the latest coding standards."
- B. "Show me how to improve the readability of this function."
- C. "Predict future coding trends and update my codebase accordingly."
- D. "Suggest ways to enhance the maintainability of this code segment."
Answer: B,D
Explanation:
Effective prompts for refactoring include requests that focus on specific quality improvements, such as readability and maintainability. These prompts guide GitHub Copilot to provide relevant and actionable suggestions.
Reference: GitHub Copilot prompt engineering best practices.
NEW QUESTION # 98
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