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GitHub GitHub-Copilot Exam Overview:

Certification Vendor:GitHub, Microsoft
Exam Name:GitHub Copilot Certification Exam
Exam Number:GH-300
Exam Format:Multi-select, Scenario-based, Case study, Multiple-choice
Real Exam Qty:60–65
Exam Duration:100 minutes
Passing Score:700 / 1000 (approx. 70%)
Exam Price:$99 USD
Certificate Validity Period:24 months
Available Languages:Spanish, Japanese, Korean, English, Portuguese (Brazil)
Recommended Training:GitHub Official Documentation
GitHub Copilot Learning Path
Exam Registration:Official GitHub Certification Page
Pearson VUE Registration
Sample Questions:GitHub GitHub-Copilot Sample Questions
Exam Way:Online proctored or in-person at Pearson VUE test centers
Pre Condition:No mandatory prerequisites; recommended: foundational GitHub knowledge, experience with at least one programming language, hands-on use of Copilot
Official Syllabus URL:https://learn.github.com/certification/COPILOT

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Reliable GitHub-Copilot Study Notes - Exams GitHub-Copilot Torrent

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GitHub GitHub-Copilot Exam Syllabus Topics:

TopicDetails
Topic 1
  • Testing with GitHub Copilot: This section of the exam measures skills of QA Engineers and Test Automation Specialists and covers AI-assisted testing methodologies, including the generation of unit tests, integration tests, and edge case detection. It explains how GitHub Copilot improves test effectiveness by suggesting relevant assertions and boilerplate test cases. The section also discusses privacy considerations, organizational code suggestion settings, and best practices for configuring GitHub Copilot’s testing features.
Topic 2
  • GitHub Copilot Plans and FeaturesThis section of the exam measures the skills of Software Engineers and IT Administrators and covers different GitHub Copilot plans, including Individual, Business, and Enterprise editions. It explains the integration of GitHub Copilot within IDEs and discusses key features such as inline chat, multiple suggestions, and exception handling. The section details the policies for managing GitHub Copilot within organizations, including auditing logs and API management. It also highlights advanced functionalities like knowledge bases for improved code quality and best practices for Copilot Chat usage.
Topic 3
  • Responsible AI: This section of the exam measures the skills of AI Ethics Analysts and AI Developers and covers the principles of responsible AI usage, the risks associated with AI, and the limitations of generative AI tools. It includes the importance of validating AI-generated outputs and operating AI systems responsibly. It also explores potential harms such as bias, privacy concerns, and fairness issues, along with methods to mitigate these risks. The ethical considerations of AI development and deployment are also discussed.
Topic 4
  • Prompt Engineering: This section of the exam measures skills of AI Engineers and Software Developers and covers the fundamentals of prompt engineering, including key principles, techniques, and best practices for generating high-quality outputs. It explains different prompting strategies such as zero-shot and few-shot prompting, how context influences AI-generated responses, and the role of structured prompts in guiding Copilot's behavior. It also discusses the prompt lifecycle and ways to enhance model performance through refined input instructions.
Topic 5
  • Developer Use Cases for AI: This section of the exam measures skills of Full-Stack Developers and Cloud Engineers and covers how AI enhances developer productivity across various tasks such as learning new programming languages, debugging, writing documentation, and refactoring code. It discusses how GitHub Copilot integrates with the Software Development Lifecycle (SDLC) and its role in modernizing legacy applications. It also highlights the use of AI for personalized responses, sample data generation, and improving overall efficiency in software development.
Topic 6
  • Privacy Fundamentals and Context Exclusions: This section of the exam measures skills of Cybersecurity Specialists and Compliance Officers and covers privacy safeguards and content exclusion settings in GitHub Copilot. It explains how Copilot can identify security vulnerabilities, suggest optimizations, and enforce secure coding practices. It also includes details on content ownership, data filtering mechanisms, and exclusion configurations. The section concludes with troubleshooting guidelines for managing context exclusions and ensuring compliance with organizational security policies.

GitHub CopilotCertification Exam Sample Questions (Q98-Q103):

NEW QUESTION # 98
What content can be configured to be excluded with content exclusions? (Each correct answer presents part of the solution. Choose three.)

Answer: C,D,E

Explanation:
Content exclusions allow you to exclude files, folders, and repositories from being used by GitHub Copilot.


NEW QUESTION # 99
Which of the following GitHub Copilot Business related activities can be tracked using the organization audit logs?

Answer: B

Explanation:
Organization audit logs track changes to content exclusion settings, providing administrators with visibility into configuration changes.


NEW QUESTION # 100
An Organization wants to adopt GitHub Copilot to support their developer in writing code. Which of the following statements best describes the responsible AI operation?

Answer: C

Explanation:
Responsible AI operation involves transparency, oversight, and security. By enforcing human review and applying security best practices, teams can ensure responsible AI operation and Accountability.
Reference:
https://learn.microsoft.com/en-us/training/modules/responsible-ai-with-github-Copilot/5-summary?ns-enrollment-type=learningpath&ns-enrollment-id=learn.github-Copilot


NEW QUESTION # 101
When using GitHub Copilot Chat to generate boilerplate code for various test types, how can you guide the AI to follow the testing standards of your company?

Answer: A

Explanation:
Providing concrete examples of your company's test structure and standards within the prompt steers Copilot Chat to generate boilerplate that aligns with your guidelines.


NEW QUESTION # 102
What is the primary role of the /optimize slash command in Visual Studio?

Answer: A

Explanation:
The /optimize slash command in Visual Studio enhances the performance of the selected code by analyzing its runtime complexity and suggesting improvements.


NEW QUESTION # 103
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