Exam Details
Microsoft · GH-300
Prepare for GH-300: Master GitHub Copilot features, prompt engineering, and responsible AI-assisted development.
Overview
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FAQ
The GH-300 certification validates your ability to use GitHub Copilot effectively across software development workflows. This exam targets developers who leverage Copilot's code generation, chat, and productivity features within their IDE. You'll demonstrate proficiency in responsible AI usage, prompt engineering, understanding Copilot's data and architecture, improving developer productivity, and configuring privacy and content exclusions. As AI-assisted development becomes standard practice, developers who can maximize Copilot's value while maintaining code quality stand out.
You're a fit for GH-300 if you:
Not sure if you're ready? Try a free sample quiz: 10 questions, instant results, identify weak areas.
| Domain | Weight | What This Means |
|---|---|---|
| Use GitHub Copilot responsibly | 15–20% | Understand responsible AI principles, Copilot's limitations, and when not to trust AI-generated code |
| Use GitHub Copilot features | 25–30% | Know Copilot's plans, features, and where it fits across the GitHub ecosystem including Copilot Chat and inline suggestions |
| Understand GitHub Copilot data and architecture | 10–15% | Understand how Copilot handles data, what it sends to the model, and how the suggestion pipeline works |
| Apply prompt engineering and context crafting | 10–15% | Write effective prompts, use Copilot Chat, and apply prompt patterns that reliably produce useful code |
| Improve developer productivity with GitHub Copilot | 10–15% | Use Copilot to accelerate coding, testing, debugging, documentation, and code review workflows |
| Configure privacy, content exclusions, and safeguards | 10–15% | Set up content exclusions, manage organizational policies, and configure what Copilot can and cannot access |
You're probably ready if you can:
You might need more prep if:
If this feels too advanced:
If you know the basics but want to build confidence:
The exam typically lasts between 100 and 120 minutes. It consists of multiple-choice questions, multiple-response questions, and scenario-based case studies designed to test your practical knowledge of GitHub Copilot in real-world development environments.
To pass the GH-300 exam, you must achieve a scaled score of 700 out of 1000. This score is not a simple percentage of correct answers; rather, it is calculated based on the relative difficulty of the specific questions presented in your exam instance.
The exam content is distributed across seven primary domains to ensure a comprehensive understanding of the tool:
Preparation should include a combination of official Microsoft Learn modules, GitHub documentation, and hands-on practice within an IDE. ExamOS offers scenario-based practice quizzes that build real exam confidence by simulating the types of decision-making challenges you will face during the actual test.
The standard registration fee for the Microsoft GH-300 exam is $165 USD. Prices may vary based on your specific country or region due to local taxes and currency exchange rates. Some organizations or academic institutions may provide vouchers to reduce this cost.
If you do not achieve a passing score on your first attempt, you must wait at least 24 hours before rescheduling. For any subsequent attempts, a 14-day waiting period is mandatory between exams. You are permitted a maximum of five exam attempts within a 12-month period.
The GitHub Copilot certification is valid for one year from the date of passing. To maintain your certified status, you can complete a free online renewal assessment through Microsoft Learn within the six months prior to your certification's expiration date.
This exam is intended for developers, DevOps engineers, and technical leads who want to demonstrate proficiency in AI-assisted workflows. There are no formal prerequisites, though candidates should have a solid foundation in:
Obtaining this certification demonstrates that you are an early adopter of AI-assisted engineering, which can make your workflow more efficient than traditional developers. However, it is not a "silver bullet" for employment. Employers view this as a specialized skill that complements, rather than replaces, core engineering logic and security awareness. Its primary value lies in proving you can leverage AI to reduce technical debt and accelerate delivery without compromising code quality.
After mastering GitHub Copilot, you may want to broaden your expertise in the GitHub ecosystem or AI implementation. Relevant follow-up certifications include: