GH-300: GitHub Copilot Certification Practice Exams (2026)

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GH-300: GitHub Copilot Certification Practice Exams (2026)
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Preparing for the official Microsoft and GitHub GH-300 Certification Exam requires far more than memorizing keyboard shortcuts. On exam day, you are tested on realistic enterprise engineering scenarios: governance across Copilot plans, strict data privacy pipelines, Content Exclusions limitations, Intellectual Property Indemnity prerequisites, Fill-In-The-Middle context assembly, Agent Mode vs Copilot Edits boundaries, and Responsible AI safeguards.This practice exam suite provides 60 original, scenario-driven questions organized into 3 full-length practice exams (20 questions per exam, 45 minutes each, 70 percent passing score aligned with the official 700 out of 1000 GH-300 passing benchmark).Complete Coverage of All 6 Official GH-300 Exam Domains:1. Practice Exam 1 - GitHub Copilot Plans, IDE Features, Agent Mode and Responsible AI (20 Questions): Differentiate Copilot Free, Pro, Pro Plus, Business, and Enterprise capabilities, slash commands, inline chat, terminal assistance, pull request summaries, Copilot Coding Agent workflows, and Responsible AI human-in-the-loop verification.2. Practice Exam 2 - Data Privacy, Content Exclusions, IP Indemnity and Prompt Engineering (20 Questions): Trace zero-retention prompt processing on Business and Enterprise plans, configure repository and organization Content Exclusions, understand why cross-file IDE type hover leaks bypass server exclusions, preserve Intellectual Property Indemnity coverage, and engineer zero-shot, few-shot, and repository custom instruction prompts.3. Practice Exam 3 - LLM Pipeline Architecture, FIM, Premium Requests, Unit Testing and Metrics API (20 Questions): Master prefix-suffix Fill-In-The-Middle context windows, Enterprise Knowledge Base Retrieval-Augmented Generation, monthly Premium Request multipliers, edge-case unit test and security remediation workflows, and Copilot Metrics API plus CLI governance.Every question includes a realistic workplace scenario, four balanced technical options, a comprehensive root-cause explanation, and itemized rationales explaining why the correct option works and why every distractor fails.Disclaimer: These unofficial practice exams are independently created by Longwave AI Lab for exam preparation and are not affiliated with, endorsed by, or sponsored by Microsoft Corporation or GitHub Inc.

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