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Free GitHub-Copilot Brain Dumps - Latest GitHub-Copilot Exam Objectives
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GitHub GitHub-Copilot Exam Syllabus Topics:
Topic
Details
Topic 1
- How GitHub Copilot Works and Handles DataThis 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 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
- 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
- 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 5
- 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.
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Latest GitHub-Copilot Exam Objectives | Exam GitHub-Copilot Overview
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GitHub CopilotCertification Exam Sample Questions (Q31-Q36):
NEW QUESTION # 31
What should developers consider when relying on GitHub Copilot for generating code that involves statistical analysis?
- A. GitHub Copilot will automatically correct any statistical errors found in the user's initial code.
- B. GitHub Copilot's suggestions are based on statistical trends and may not always apply accurately to specific datasets.
- C. GitHub Copilot can independently verify the statistical significance of results.
- D. GitHub Copilot can design new statistical methods that have not been previously documented.
Answer: B
Explanation:
Developers should consider that GitHub Copilot's suggestions are based on statistical trends and may not always be accurate for specific datasets, requiring careful validation.
NEW QUESTION # 32
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)?
- A. GitHub Copilot Teams
- B. GitHub Copilot Individual
- C. GitHub Copilot Enterprise
- D. GitHub Copilot Business for non-GHE customers
Answer: C
Explanation:
GitHub Copilot Enterprise is the most cost-effective plan for managing users with an Identity Provider like Okta, as it provides enterprise-level features and integration.
NEW QUESTION # 33
GitHub Copilot in the Command Line Interface (CLI) can be used to configure the following settings: (Each correct answer presents part of the solution. Choose two.)
- A. The default execution confirmation
- B. The default editor
- C. Usage analytics
- D. GitHub CLI subcommands
Answer: A,C
Explanation:
GitHub Copilot in the CLI allows configuration of settings such as the default execution confirmation and usage analytics. These settings help tailor the CLI experience to the user's preferences.
NEW QUESTION # 34
What practices enhance the quality of suggestions provided by GitHub Copilot? (Select three.)
- A. Use a .gitignore file to exclude irrelevant files
- B. Providing examples of desired output
- C. Using meaningful variable names
- D. Clearly defining the problem or task
- E. Including personal information in the code comments
Answer: B,C,D
Explanation:
The quality of Copilot's suggestions is enhanced by clearly defining the task, using meaningful variable names, and providing examples of the desired output.
NEW QUESTION # 35
How can you get multiple suggestions from GitHub Copilot?
- A. By using the inline chat functionality with the command 'multiple'
- B. By using @workspace in the chat window
- C. By asking for multiple suggestions using comments in your code
- D. By opening the completions panel in your editor
Answer: D
Explanation:
You can get multiple suggestions by opening the completions panel in your editor, which displays alternative code suggestions.
NEW QUESTION # 36
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