GitHub Copilot Certification (GH-300) — Study Guide
A free, independent study guide for the official GitHub Copilot certification. Six topic guides — written for experienced developers who already use Copilot and want to validate that knowledge with a recognized credential.
Version scope: this guide uses the January 2026 study-guide baseline. Check the official GH-300 study guide for current objectives and exam requirements before booking.
Why this study guide?
GitHub's official GH-300 study guide tells you what the exam covers. This guide tells you how to actually study it — domain by domain, weighted by exam importance, with the same methodology AI Architect Mastery teaches in its AI Driven Development courses.
What you get here:
- Organized around the January 2026 study-guide baseline — compare the topics and weights below with the current official objectives; this is not a guarantee of complete current exam coverage or a passing result
- Written for experienced developers — no beginner fluff, no AI hype, no marketing
- Exam-ready summaries — every module ends with a checklist of what you must remember in the exam
- Honest about Copilot's limits — privacy, plan differences, preview features, deprecated modes (Edit Mode → Agent Mode)
- Linked to authoritative sources — every module ends with the official GitHub and Microsoft Learn references
Want structured video lessons and chapter quizzes?
The GitHub Copilot GH-300 Certification Prep course includes video lectures, coding demos, written materials and a practice test. Check Udemy for current availability and pricing.
The Six Modules
These six modules use the January 2026 baseline and its listed exam weights. Use the current official objectives, along with your own knowledge gaps, to prioritize study.
Responsible AI
Risks, limitations, and ethical use of generative AI. The six principles of responsible AI and how they apply to GitHub Copilot in real development work.
Exam weight: 15–20% Read module → M02GitHub Copilot Features
Copilot in the IDE, CLI, agent mode, plan mode, MCP, code review, Spaces, Spark, cloud agent, memory, and organization-level governance — the largest exam domain.
Exam weight: 25–30% Read module → M03Data and Architecture
How Copilot handles your data, the suggestion lifecycle, the proxy filtering pipeline, plan-level differences in training data use, and the technical limitations of LLMs.
Exam weight: 10–15% Read module → M04Prompt Engineering & Context
The anatomy of an effective prompt (Role + Task + Context + Format), zero-shot vs. few-shot, chain-of-thought, role prompting, and how to manage Copilot's context window.
Exam weight: 10–15% Read module → M05Developer Productivity
Where Copilot saves the most time: code generation, refactoring, documentation, test generation, edge case detection, and security improvements — with realistic limits.
Exam weight: 10–15% Read module → M06Privacy & Safeguards
Content exclusions (org > repo > user), duplication detection, security warnings, IDE settings, plan-level differences, and a working troubleshooting checklist.
Exam weight: 10–15% Read module →Exam logistics — at a glance
| Item | Detail |
|---|---|
| Exam name | GitHub Copilot — GH-300 |
| Format | Online proctored or test center (Pearson VUE) |
| Duration | ~45–75 minutes |
| Pass score | 700 / 1000 |
| Validity | 1 year |
| Official guide | GH-300 Study Guide (aka.ms) |
| Exam sandbox | GitHub Exam Demo |
| Registration | examregistration.github.com |
How to use this guide
- Start with M01 — Responsible AI. It is the conceptual foundation and around 1 in 5 exam questions tests it.
- Spend the most time on M02 — Copilot Features. Roughly 1 in 4 questions comes from this domain.
- Read M03–M06 in order. Each builds on the previous module.
- Use the official exam sandbox after finishing M06.
- Re-read each module's "Exam-ready checklist" the day before the exam.
Related: structured AI development methodology
Passing the certification is one milestone — but using GitHub Copilot well in production is a methodology question. AI Architect Mastery teaches the AI Driven Development Methodology — a human-led, vendor-neutral workflow (PRD → PLAN → TASK → IMPLEMENTATION). Read the methodology reference for responsibilities, bounded work and evidence-based human decisions. The method does not guarantee production readiness.
Video lessons, quizzes, and a structured pacing plan
The GitHub Copilot GH-300 Certification Prep course on Udemy includes video lectures, coding demos, written materials and a practice test. Course exercises are not official exam questions.
Source & responsibility: Maintained by AI Architect Mastery, using the official GH-300 study guide as the January 2026 baseline. Each domain guide links its technical references. Product features and exam requirements may change; consult the official sources for current details.