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GitHub GitHub-Copilot Exam Overview:

Certification Vendor:GitHub
Exam Name:Microsoft GitHub Copilot
Exam Number:GH-300
Real Exam Qty:60-65
Passing Score:700 / 1000
Available Languages:English
Exam Format:Multiple Choice
Related Certifications:GitHub Copilot Certified Professional
Certificate Validity Period:2 years
Exam Duration:100 minutes
Exam Price:$99 USD
Sample Questions:GitHub GitHub-Copilot Sample Questions
Exam Way:Proctored (Online or Offline Test Centers)
Official Syllabus URL:https://learn.microsoft.com/en-us/credentials/certifications/github-copilot

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This GitHub CopilotCertification Exam (GitHub-Copilot) software has a simple-to-use interface. By using the GitHub-Copilot practice exam software, you can evaluate your mistakes at the end of every take and overcome them. Our software helps you to get familiar with the format of the original GitHub-Copilot test. Software lets you customize your GitHub GitHub-Copilot Practice Exam's duration and question numbers as per your practice needs. You just need an active internet connection to confirm the license of your product. All Windows-based computers support this GitHub-Copilot practice exam software.

GitHub GitHub-Copilot Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • 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 3
  • 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 4
  • How GitHub Copilot Works and Handles Data: This section of the exam measures the skills of Data Security Specialists and DevOps Engineers and covers how GitHub Copilot processes data, handles code suggestions and manages privacy concerns. It explains the data pipeline for Copilot’s suggestions, how it gathers context, and how prompts are processed through its AI model. The section also discusses the limitations of AI-generated code, the effects of historical data on suggestions, and the role of prompt crafting. Best practices for improving prompt effectiveness and optimizing AI-generated responses are included.
Topic 5
  • 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.

GitHub CopilotCertification Exam Sample Questions (Q106-Q111):

NEW QUESTION # 106
Which Copilot Individual features are available when using a supported extension for Visual Studio, VS Code, or JetBrains IDEs? (Each correct answer presents part of the solution. Choose two.)

Answer: C,D


NEW QUESTION # 107
A team is using GitHub Copilot Individual in their daily development activities. They need to exclude specific files from being used to inform code completion suggestions. How can they achieve this?

Answer: C

Explanation:
Content exclusion (the ability to block specific files from influencing Copilot's suggestions) isn't available on the Individual plan. You must be on a business‑level subscription - e.g. GitHub Copilot Business - to use content exclusion settings.


NEW QUESTION # 108
A company is currently storing code in Bitbucket and would like to use GitHub Copilot. Which GitHub Copilot plan will be most cost effective to allow them to manage users with their Identity Provider (e.g. Okta)?

Answer: D

Explanation:
For organizations that do not have a GitHub Enterprise Cloud (GHEC) subscription, the GitHub Copilot Business plan is indeed the most cost-effective option that supports an Identity Provider (IdP) like Okta.
Why this plan fits:
Cost: At $19 USD per user/month, it is significantly cheaper than the Copilot Enterprise plan ($39 USD per user/month).
IdP Support: It provides SAML SSO support, allowing you to manage user access through Okta even if your code is hosted elsewhere (e.g., Bitbucket).
No GHEC Requirement: Unlike the "Enterprise" tier, this specific SKU allows you to provide enterprise-style identity and access management without a full GitHub Enterprise setup.
Reference:
https://dev.to/codewithsimon/what-is-github-copilot-and-how-can-it-boost-your-productivity-14gg


NEW QUESTION # 109
How can you improve the context used by GitHub Copilot? (Each correct answer presents part of the solution. Choose two.)

Answer: B,D

Explanation:
Improving the context for GitHub Copilot involves opening relevant files in your IDE to provide immediate context and adding relevant code snippets directly to your prompts to give Copilot specific examples and information.


NEW QUESTION # 110
Which of the following scenarios best describes the intended use of GitHub Copilot Chat as a tool?

Answer: B

Explanation:
GitHub Copilot Chat is designed to be a productivity enhancer, not a replacement for human developers. It provides suggestions and assists with coding tasks, but the final decision and validation always rest with the developer. Copilot Chat is meant to augment the developer's workflow, making it faster and more efficient, but it does not remove the need for human oversight and judgment.


NEW QUESTION # 111
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