Azure Mastery
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Azure Mastery
Microsoft Certification GH-300
On-device AI scores your readiness, builds an adaptive study plan, and flags topics fading from memory — before they cost you the exam.
Get exam-ready for GH-300 (GitHub Copilot) on iPhone or iPad. Azure Mastery uses on-device AI to predict your readiness score, build a personalised study plan around the six GitHub Copilot domains, and surface topics you're forgetting — all without sending a single byte off your device.
The exam
GH-300 is the GitHub Copilot certification — an intermediate credential for developers and technical team members who already use Copilot and want to prove real, applied expertise. It's owned and maintained by GitHub but delivered through Microsoft's exam platform, and it assumes you already have GitHub fundamentals and experience in at least one programming language. This is not a beginner exam: it validates that you can use GitHub Copilot responsibly, work fluently with Copilot's features across the IDE, CLI and beyond, understand how Copilot processes your data, craft effective prompts, and configure the right privacy and safeguards.
GH-300 is applied rather than purely conceptual — it expects a working model of how Copilot fits into a real development workflow: inline suggestions and Copilot Chat, the Copilot CLI, Agent Mode, Edit Mode and MCP, code review, and organization-wide policy management. It also tests the judgement around the tool: why you must validate AI output before trusting it, how prompt context is determined, when duplication detection and content exclusions matter, and how to read the security warnings Copilot surfaces.
The GH-300 skills outline was last updated as of January 2026. Every question in Azure Mastery's GH-300 bank is mapped to the current six-domain outline — including newer surfaces such as Plan Mode, Agent Mode, MCP, and Spaces and Spark — with no leftover questions on retired features. Read the official study guide at learn.microsoft.com.
Skills measured · January 2026
Six domains, with weights from GitHub's skills outline as of January 2026. Every domain summary below is paraphrased from the official study guide; the bullet-level objectives in Azure Mastery are tagged so you always know which domain you're being tested on.
The judgement domain. Covers the risks and limitations of generative AI, ethical and responsible AI use, and how to identify potential harms and their mitigations. Most importantly, it tests why you must validate Copilot's output before you trust it — recognising biased, insecure, or simply wrong suggestions, and knowing how a professional responds. Get this mindset right and the rest of the exam makes sense.
The largest domain. Copilot inside the IDE — inline suggestions, Copilot Chat, the Copilot CLI, and Plan Mode — plus Agent Mode, Edit Mode, and MCP for tool-connected workflows. Also covers using Copilot in code review, Spaces and Spark, and organization-wide policy management. Expect scenario questions on which feature fits which task and how they combine.
What happens under the hood: how your data is used, flows, and is shared; input processing and prompt building; the proxy service that handles filtering and post-processing; and the full code-suggestion lifecycle from keystroke to accepted suggestion. Also covers the limitations of the underlying large language models so you know what Copilot can and cannot do.
Getting better suggestions on purpose: prompt structure and the role of context, how Copilot determines the context it uses, and the difference between zero-shot and few-shot prompting. Rounds out with the core principles of prompt engineering — being specific, giving examples, and iterating — so you can steer Copilot rather than accept whatever it offers first.
Copilot applied to real work: generating code, refactoring, and writing documentation; accelerating how you learn a new codebase or language; generating tests and finding edge cases; and using Copilot to improve the security and performance of existing code. This domain is about outcomes — turning Copilot from an autocomplete into a genuine productivity multiplier.
The controls that keep Copilot safe to use: content exclusions and editor settings, the ownership and limitations of Copilot's outputs, duplication detection to avoid matching public code, and the security warnings Copilot raises. Expect questions on configuring exclusions at the repository and organization level and what each safeguard actually protects.
Designed for GH-300
Azure Mastery ships with 355 GH-300 practice questions, every one written specifically against the current GitHub Copilot skills outline — not generic Copilot trivia. Each question carries a domain tag mapped to the official six domains, so you always know which area you're being tested on and where your weak spots are clustered.
The on-device Exam IQ engine predicts your GH-300 score before you sit the exam. After roughly 30 questions it has enough signal to give a confidence-scored prediction (e.g. "786 ±37, 68% confidence") — and tells you the specific topics that are dragging your readiness down. No vague "study more" advice; just a ranked list of objectives where improvement would move your score the furthest.
The adaptive study plan rebuilds itself from your answer history. Get something wrong on content exclusions? You'll see another content-exclusion question in the next session. Nail "when to use Agent Mode vs Edit Mode" three sessions running and the engine backs off, surfacing newer material such as the code-suggestion lifecycle or few-shot prompting. The plan optimises for the gap between where you are and the 700 pass score, not for blind volume.
Knowledge decay tracking is the secret weapon for a broad, applied exam like GH-300. The same domain you mastered six weeks ago is the domain you'll forget by exam day if you stop revising. Azure Mastery tracks every topic's decay curve and flags topics approaching expiry — the padlock icon on the Today screen is your "revisit before you forget" cue.
Real exam simulation mode runs at GH-300's actual length and time pressure: a randomised question set drawn from the full 355-question bank, a ~90-minute timer, no jumping back to flag-and-review. It's the closest you can get to the test centre experience without sitting the exam.
Everything runs on-device. Your answer history, your readiness gauge, your decay alerts — none of it leaves your iPhone or iPad. No account required to start, no tracking, no sync server. Privacy-first by design.
2-week revision plan
If you already use GitHub Copilot day to day, most candidates pass GH-300 after one to two weeks of focused revision. Below is a two-week plan that maps onto Azure Mastery's six domains, simulator, and decay alerts. Adjust pace to taste — the readiness gauge tells you when you're done, not the calendar.
Frequently asked
The GitHub Copilot exam is roughly USD $99, though the exact price varies by region. GH-300 runs about 90 minutes and you need 700 out of 1000 to pass. It's delivered through Microsoft's exam platform, but the certification itself is owned and maintained by GitHub. Check the official GitHub Copilot page for current pricing and any active promotions before you book.
GitHub credentials are valid for two years and are renewed by re-examination — so once you pass GH-300 you stay certified for two years, then re-take the exam to keep the credential current. The certification is delivered by Microsoft but owned and maintained by GitHub, which sets this two-year validity.
GH-300 is an intermediate-level certification for developers and technical team members who already use GitHub Copilot day to day and want to prove real, applied expertise. It assumes GitHub fundamentals and experience in at least one programming language. This is not a beginner exam — it validates working knowledge of Copilot's features, data flows, prompt engineering, and responsible-use practices.
Yes. "Use GitHub Copilot Responsibly" is the first domain, weighted 15–20%. It tests the risks and limitations of generative AI, ethical and responsible AI use, how to identify potential harms and their mitigations, and — critically — why you must validate Copilot's output before trusting it. Expect scenario questions about biased or insecure suggestions and how a professional handles them.
Prompt engineering and context crafting is its own domain, weighted 10–15%. GH-300 tests how you structure a prompt, how Copilot determines context, the difference between zero-shot and few-shot prompting, and the core principles of writing prompts that produce useful, relevant suggestions. It pairs closely with the data-and-architecture domain, which explains how your prompt is processed and turned into a suggestion.
Azure Mastery ships with 355 GH-300 practice questions, each mapped to one of the six official GitHub Copilot domains — from responsible AI and Copilot features to data and architecture, prompt engineering, developer productivity, and privacy with content exclusions. Everything runs on-device: your answer history and readiness gauge never leave your iPhone or iPad.
Download Azure Mastery free. 355 GH-300 practice questions, AI score prediction, and a personalised study plan that adapts to your weak spots. iPhone & iPad.
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