GitHub Copilot Certification (GH-300) — Study Guide
A free, structured study guide for the official GitHub Copilot certification. Six modules covering every exam domain — written for experienced developers who already use Copilot and want to validate that knowledge with a recognized credential.
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:
- Aligned to the official January 2026 study guide — every exam domain covered, in the order and weight the exam tests them
- 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
Companion to the AAM Udemy course. This documentation is the open-access reference material for the upcoming AI Architect Mastery GH-300 preparation course on Udemy. The course adds video walk-throughs, demos, chapter quizzes, and a structured pacing plan — but every fact you need is here, free.
The Six Modules
The GH-300 exam has six domains, weighted by exam share. Spend the most time on M01 and M02 — together they account for roughly half of the exam.
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 — also known as structured Vibe Coding — a structured, agent-driven workflow (PRD → PLAN → TASK → IMPLEMENTATION) that turns ad hoc Copilot use into a repeatable, production-quality method.
See the methodology See AAM courses
Source & versioning: This documentation is maintained in the
docs/resources/c008/source documentation/ tree of the AAM internal-material
repository. Aligned to the GH-300 study guide as of January 2026 (last content update: April 2026).