GitHub Copilot (GH-300) Practice Test

The GH-300 is designed for software developers, DevOps engineers, app makers, and technology managers who use or oversee GitHub Copilot in professional development environments. Candidates are expected to have hands-on experience with at least one programming language and a working familiarity with GitHub fundamentals such as repositories, pull requests, and GitHub Actions.

The certification is particularly relevant for developers looking to formalize their AI-assisted development skills, team leads responsible for rolling out Copilot across engineering organizations, and enterprise administrators who configure organization-wide Copilot policies, content exclusions, and audit logging. It is not an entry-level exam — candidates should already be comfortable using an IDE and have some exposure to GitHub Copilot before attempting the certification.

There are no formal prerequisites required to register for the GH-300 exam. However, Microsoft recommends that candidates have familiarity with GitHub fundamentals and practical experience with one or more programming languages before attempting the exam.

Recommended preparation includes completing the official Microsoft Learn learning paths — 'GitHub Copilot Fundamentals Part 1' and 'GitHub Copilot Fundamentals Part 2' — and the instructor-led course GH-300T00-A (a one-day intermediate course). Candidates should also review the official GitHub documentation on Copilot plans, data handling, prompt engineering, and privacy/content exclusion configuration. Prior exposure to responsible AI concepts, such as identifying risks and mitigation strategies for generative AI tools, is strongly recommended given the 15–20% exam weight on that domain.

The GH-300 exam is 100 minutes in duration and delivered through Pearson VUE as a proctored assessment. The exam may include interactive components in addition to traditional question types. The exact number of questions is not publicly disclosed by Microsoft, though the format is consistent with other GitHub certifications. A score of 700 or greater (on a scale that Microsoft does not publicly define as a fixed number of questions) is required to pass.

The exam is available online (remotely proctored) or at in-person Pearson VUE test centers. If a candidate fails, they must wait 24 hours before retaking; subsequent retake waiting periods vary per Microsoft's retake policy. An exam sandbox is available at GHCertDemo.starttest.com so candidates can preview the interface and question types before test day. Accommodations for extra time or assistive devices can be requested through Microsoft's credentials support portal.

• 1.Use GitHub Copilot Responsibly (15–20%): Covers responsible AI principles including risks and limitations of generative AI, ethical usage, potential harms and mitigation strategies, validation of AI outputs, and operating Copilot responsibly.
• 2.Use GitHub Copilot Features (25–30%): Covers enabling and triggering Copilot in the IDE (inline suggestions, chat, CLI, Plan Mode), using Copilot CLI for scripting and file management, Agent Mode, Edit Mode, MCP integrations, Agent Sessions, Sub-Agents, Copilot for code review, Spaces, Spark, Pull Request summaries, instruction files, and managing organization-wide policies via audit logs and REST API.
• 3.GitHub Copilot Features — Overlap/Detail Domain (25–30%): As listed in the official study guide, this second 'Use GitHub Copilot features' domain reinforces feature capabilities including Copilot Chat commands, prompt file reuse, Copilot Code Review policies, and feature availability management across IDEs and github.com.
• 4.Understand GitHub Copilot Data and Architecture (10–15%): Covers data usage, flow and sharing, input processing and prompt building, proxy filtering, post-processing, code suggestion lifecycle, and limitations of the underlying large language models (LLMs).
• 5.Apply Prompt Engineering and Context Crafting (10–15%): Covers prompt structure, context determination, zero-shot and few-shot prompting techniques, best practices for effective prompts, prompt engineering principles, and chat history usage.
• 6.Improve Developer Productivity with GitHub Copilot (10–15%): Covers using Copilot for code generation, refactoring, documentation, accelerating learning, reducing context switching, generating sample data, modernizing legacy code, generating unit and integration tests, identifying edge cases, writing assertions, and suggesting security and performance improvements.
• 7.Configure Privacy, Content Exclusions, and Safeguards (10–15%): Covers configuring content exclusions and editor settings, output ownership and limitations, enabling duplication detection and security warnings, and troubleshooting suggestion and exclusion issues.

• Complete both official Microsoft Learn paths — 'GitHub Copilot Fundamentals Part 1' and 'GitHub Copilot Fundamentals Part 2' — before anything else, as they map directly to the exam domains and were updated alongside the January 2026 exam revision.
• Use the official exam sandbox at GHCertDemo.starttest.com to familiarize yourself with the question interface, including any interactive components, so the format is not a surprise on test day.
• Take the official Microsoft Learn practice assessment (assessmentId 218035372, linked from the certification page) multiple times to identify weak areas across domains, especially the two high-weight 'Use GitHub Copilot Features' domains at 25–30% each.
• Hands-on practice is critical — set up GitHub Copilot in VS Code or a JetBrains IDE, experiment with Agent Mode, Edit Mode, Copilot Chat, and the CLI, and practice writing zero-shot and few-shot prompts to internalize prompt engineering concepts rather than just reading about them.
• Study the official GitHub documentation on content exclusions (docs.github.com/copilot/managing-copilot/configuring-and-auditing-content-exclusion) and the GitHub Trust Center (github.com/trust-center) for the data architecture domain, as these are primary sources for questions on privacy, proxy filtering, and data flow.
• Pay special attention to the January 2026 exam update changelog — new objectives around Agent Sessions, Sub-Agents, Spaces, Spark, MCP, and Copilot Code Review policies are now testable and may not be covered in older third-party study materials.
• Register for the exam using a personal Microsoft Account (MSA), not a work or school Azure AD account — if you use an organizational account and leave that organization, your exam records become permanently unrecoverable.

The GH-300 certification signals to employers that a developer can responsibly and effectively leverage GitHub Copilot — a tool now used by over 15 million developers and deployed across 90% of Fortune 100 companies. Certified professionals are positioned for roles such as software engineer, DevOps engineer, AI-augmented developer, and technology manager in organizations actively scaling AI-assisted development practices. According to GitHub's own certification impact data, 79% of certified employees produce higher quality work, 70% demonstrate improved productivity, and 32% report salary increases following certification.

Unlike cloud platform certifications (AWS, Azure) which focus on infrastructure, GH-300 is one of the few vendor-backed credentials specifically validating AI coding assistant proficiency — making it complementary rather than competitive with existing developer certifications. As AI pair programming becomes standard practice in enterprise engineering teams, this certification differentiates candidates in hiring, promotion, and consulting contexts, particularly for roles that involve onboarding teams onto Copilot, configuring enterprise Copilot policies, or advocating for responsible AI practices within engineering organizations.