GitHub GH-300 Copilot Practice Exams

About the GitHub GH-300 GitHub Copilot exam

Exam at a glance

GH-300 is the GitHub Copilot certification exam. It is published on Microsoft Learn and scheduled through Pearson VUE. It is a proctored exam at the Intermediate level, you have 100 minutes to complete it, and a score of 700 or greater out of 1000 is required to pass. Microsoft does not publish a fixed question count for GH-300.

What the exam certifies

GH-300 certifies that you can use GitHub Copilot productively and responsibly across the editor, the terminal and GitHub itself, and that you understand what happens to your code and prompts along the way. The study guide splits the work into six weighted domains:

• Use GitHub Copilot features (25–30%): enabling and triggering Copilot in the IDE through inline suggestions, chat and agent mode, installing and using GitHub Copilot CLI, working with agent mode, MCP, code review, Spaces, Spark and instructions files, and managing organization policies, audit log events and subscriptions.
• Use GitHub Copilot responsibly (15–20%): the risks and limitations of generative AI, ethical and responsible AI usage, potential harms and their mitigations, and why every Copilot output has to be validated before you rely on it.
• Understand GitHub Copilot data and architecture (10–15%): how data is used, shared and processed, how prompts are built from context, what proxy filtering and post-processing do, and the code suggestion lifecycle and limits of large language models.
• Apply prompt engineering and context crafting (10–15%): prompt structure and how context is determined, zero-shot and few-shot prompting, prompt crafting best practices, and how the prompt process flow uses chat history.
• Improve developer productivity with GitHub Copilot (10–15%): code generation, refactoring and documentation, learning faster with less context switching, sample data and legacy modernization, and generating tests, edge cases, security improvements and performance optimizations.
• Configure privacy, content exclusions, and safeguards (10–15%): content exclusions and editor settings, ownership and limitations of outputs, filtering suggestions that match public code, and resolving issues with suggestions and content exclusions.

What kind of exam it is

GH-300 is a scenario exam about fit and control. A typical item describes a developer, a team or an administrator with a goal and asks which Copilot surface, setting or practice gets them there, and the tempting option is usually a real feature applied to the wrong question, such as an editor setting offered where only a content exclusion rule works. The current outline, measured as of August 7, 2026, names recent surfaces including Copilot CLI, agent sessions and sub-agents, Spaces, Spark and prompt files, and the study guide notes that most questions cover generally available features. Microsoft does not identify question types in advance, and the certification page notes that you may have interactive components to complete.

Prerequisites

None are formally required, but the published profile assumes you already use Copilot to improve software development productivity, quality and security, understand GitHub fundamentals, and have experience with one or more programming languages.

Why take this certification

• It proves daily-use skill. Copilot is part of how many teams now write code, and the certification shows you use it deliberately rather than by trial and error.
• It covers the questions teams actually ask. Which plan and policy unlock a feature, what leaves the editor, and how to keep sensitive files out of context are the practical questions the syllabus is built around.
• It makes you faster and safer at once. The domains pair productivity with validation, responsible AI and safeguards, so the habits you build pay off in real pull requests.
• It pairs with what you have. It sits naturally alongside other GitHub credentials and general developer, DevOps or cloud certifications rather than duplicating them.

What you'll learn for the GH-300 exam

GH-300 tests whether you can pick the right Copilot feature, control or prompt for a situation, so the goal is a working model of each one and when it applies. Every free question and every premium exam maps to the six exam domains below, weighted the way the exam weights them, and each explanation covers why the right answer is right and why every distractor is wrong, citing GitHub and Microsoft Learn documentation.

Use GitHub Copilot responsibly (15–20%)

• Describe the risks and limitations of generative AI, including hallucinations, and name the responsible AI principle a scenario strains.
• Operate Copilot responsibly: scope the request, read what an agent asks you to approve, and review and test output before relying on it.
• Exam habit: fluent, confident output is not correct output; the answer that validates the proposal usually wins.

Use GitHub Copilot features (25–30%)

• Enable and trigger Copilot in the IDE through inline suggestions, chat and agent mode, and install and use GitHub Copilot CLI interactively and in sessions.
• Choose between agent mode, Copilot Edits, MCP, code review, Spaces, Spark, pull request summaries, instructions files and prompt files by where the work runs and who drives the steps.
• Manage organization-wide policies, Copilot code review policies, audit log events and subscriptions through the REST API.
• Exam habit: when a feature is missing, trace the access chain of client, sign-in, plan, seat and policy before blaming the feature.

Understand GitHub Copilot data and architecture (10–15%)

• Explain how Copilot gathers context, builds a prompt, filters it through the proxy and post-processes the response.
• Describe how data is used and shared, and visualize the code suggestion lifecycle from prompt to your accept or reject decision.
• Exam habit: separate what the request carries from what the model can know; plausible output can still be wrong.

Apply prompt engineering and context crafting (10–15%)

• Structure prompts with clear intent, relevant context and examples, and understand how Copilot determines the context it sends.
• Use zero-shot and few-shot prompting, and manage chat history so a long session does not drift.
• Exam habit: a specific target and a small, reviewable scope beat a persona or a vague "make it better".

Improve developer productivity with GitHub Copilot (10–15%)

• Use Copilot for code generation, refactoring, documentation, explanation, sample data and legacy modernization.
• Generate unit and integration tests, identify edge cases and assertions, and surface security and performance improvements.
• Exam habit: Copilot proposes and a baseline decides; compiling is not the check, running the tests is.

Configure privacy, content exclusions, and safeguards (10–15%)

• Configure content exclusions at the right scope and tell them apart from personal editor settings.
• Describe ownership and limitations of outputs, and enable filtering of suggestions that match public code.
• Exam habit: when something misbehaves, diagnose whether it is the service, the client, the network or a policy before changing any control.

How the practice exams help

Each question puts you in a concrete Copilot situation and asks for the next decision, the same shape the exam uses, so you practise matching features and controls to needs instead of memorising menu names. Detailed explanations cover every option, which is where the real learning is: the wrong answers are the plausible ones developers actually reach for.

How to prepare for the GH-300 exam

GH-300 rewards people who use Copilot every day and know why it behaves the way it does. Reading alone underprepares you, so pair the study guide with hands-on work in your own editor and repository:

1. Work the study guide domain by domain (1 to 2 weeks). Read each skill and its bullets, and use our free GH-300 study guide as the plain-language companion, with comparison tables and decision trees for choosing the right Copilot surface, control and prompt.
2. Use every surface hands-on (about 1 week). Try inline suggestions, Copilot Chat and agent mode in your editor, install GitHub Copilot CLI and run it in a session, then look at the organization settings side: policies, content exclusions and the public code filter.
3. Drill the biggest levers (about 1 week). Use GitHub Copilot features is the heaviest domain at 25 to 30 percent and responsible use carries 15 to 20 percent, so most of your review belongs there before the four domains at 10 to 15 percent each.
4. Practice exams (1 to 2 weeks). Start with the free 10-question sample above to gauge your level, then work the 25 premium practice exams, 1,497 questions in total (24 exams of 60 questions and one of 57) with a detailed explanation on every option. Take them timed, review every wrong answer, and aim for a comfortable margin above the 700 out of 1000 pass mark before you book.

Recommended timeline

3 to 5 weeks of focused study for most candidates, and less if you already use Copilot across the editor, the CLI and GitHub every day. The single biggest predictor of a pass is steady scores across all six domains on practice tests, not a strong score in the domain you already know.

Official resources

Start with the official GitHub Copilot certification page for the format and booking, and read the GH-300 study guide for the authoritative domain list and weightings. Reinforce it with our free GH-300 study guide and the practice exams on this page.

Frequently asked questions