為 GitHub CopilotCertification Exam - GitHub-Copilot 題庫客戶提供跟踪服務
我們對所有購買 GitHub GitHub CopilotCertification Exam - GitHub-Copilot 題庫的客戶提供跟踪服務，確保 GitHub GitHub CopilotCertification Exam - GitHub-Copilot 考題的覆蓋率始終都在95％以上，並且提供2種 GitHub GitHub CopilotCertification Exam - GitHub-Copilot 考題版本供你選擇。在您購買考題後的一年內，享受免費升級考題服務，並免費提供給您最新的 GitHub GitHub CopilotCertification Exam - GitHub-Copilot 試題版本。
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購買後，立即下載 GitHub-Copilot 試題 (GitHub CopilotCertification Exam): 成功付款後, 我們的體統將自動通過電子郵箱將你已購買的產品發送到你的郵箱。（如果在12小時內未收到，請聯繫我們，注意：不要忘記檢查你的垃圾郵件。）
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在IT世界裡，擁有 GitHub GitHub CopilotCertification Exam - GitHub-Copilot 認證已成為最合適的加更簡單的方法來達到成功。這意味著，考生應努力通過考試才能獲得 GitHub CopilotCertification Exam - GitHub-Copilot 認證。我們很好地體察到了你們的願望，並且為了滿足廣大考生的要求，向你們提供最好的 GitHub GitHub CopilotCertification Exam - GitHub-Copilot 考古題。如果你選擇了我們的 GitHub GitHub CopilotCertification Exam - GitHub-Copilot 考古題資料，你會覺得拿到 GitHub 證書不是那麼難了。
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GitHub GitHub-Copilot 考試大綱：
| 主題 | 簡介 |
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| 主題 1 | - 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.
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| 主題 2 | - 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.
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| 主題 3 | - 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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| 主題 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.
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| 主題 5 | - 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.
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參考：https://examregistration.github.com/certification/COPILOT
1311位客戶反饋
114.32.20.* -
如果沒有你們提供的考題，我想我會在 GitHub-Copilot 考試中失敗。 Sfyc-Ru 真的是很好的學習網站。當我購買了你們的考題，我就輕松的通過了我的考試。