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GitHub GitHub-Copilot Exam Overview:

Certification Vendor:GitHub
Exam Name:Microsoft GitHub Copilot
Exam Number:GH-300
Certificate Validity Period:2 years
Passing Score:700 / 1000
Real Exam Qty:60-65
Exam Price:$99 USD
Available Languages:English
Exam Format:Multiple Choice
Exam Duration:100 minutes
Related Certifications:GitHub Copilot Certified Professional
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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GitHub GitHub-Copilot Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • 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 3
  • 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 4
  • 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.
Topic 5
  • 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.

GitHub CopilotCertification Exam Sample Questions (Q68-Q73):

NEW QUESTION # 68
Identify the right use cases where GitHub Copilot Chat is most effective. (Each correct answer presents part of the solution. Choose two.)

Answer: B,C

Explanation:
GitHub Copilot Chat is effective for explaining and translating legacy code and generating unit test scenarios for new code.


NEW QUESTION # 69
How does GitHub Copilot assist developers in minimizing context switching?

Answer: C

Explanation:
By surfacing code suggestions and documentation directly in your editor, Copilot keeps you working within your IDE and reduces the need to switch to external resources.


NEW QUESTION # 70
Which of the following GitHub Copilot Business related activities can be tracked using the organization audit logs?

Answer: A

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


NEW QUESTION # 71
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: A,C


NEW QUESTION # 72
Why might a Generative AI (Gen AI) tool create inaccurate outputs?

Answer: B

Explanation:
Gen AI tools can produce inaccurate outputs if the training data contains biases or inconsistencies, which can lead to flawed or misleading results.


NEW QUESTION # 73
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