- Risks and limitations of generative AI tools.
- Ethical and responsible AI use, and the harms to watch for.
- Why you must validate AI output before you ship it.
- How to operate GitHub Copilot responsibly on a team.
GitHub Certification Training Course
GitHub Copilot (GH-300) Certification Training Course
Get real productivity from GitHub Copilot, roll it out safely to your team, and get ready for the GitHub Copilot (GH-300) exam with Accumentum’s live online training.
Course focus: Use GitHub Copilot responsibly across the IDE, chat, CLI and agent mode, write better prompts, configure privacy and policy settings, and prepare for the GitHub Copilot (GH-300) exam.
Course Overview
Use GitHub Copilot well and roll it out to your team with the right guardrails.
Most teams have turned GitHub Copilot on. Far fewer use it well. This course is for developers who want better results from Copilot and for the leads who have to roll it out across a team. We cover how Copilot works, how to prompt it, and how to set the policies that keep it safe.
The course follows the official GH-300 skills outline. You will use Copilot in the IDE, in chat, in the CLI and in agent mode, work with MCP, code review and instructions files, and learn how Copilot handles your data. We also cover content exclusions, public code filtering and organization-wide policy.
By the end you will write better prompts, check Copilot’s output with a critical eye, and know which settings to turn on for your organization. You will also be ready to sit the GitHub Copilot exam.
Course Objectives
Build GitHub Copilot skills and GH-300 exam readiness.
01
Responsible AI Use
Understand the risks and limits of generative AI and why every Copilot suggestion needs to be checked.
02
Copilot Features
Use Copilot in the IDE, chat, CLI and agent mode, plus code review, Spaces and pull request summaries.
03
Prompting and Productivity
Write clear prompts with the right context and use Copilot for code, tests, refactoring and documentation.
04
GH-300 Exam Readiness
Cover all six domains in the official GH-300 skills outline, including data handling, privacy and organization policy.
Who Should Attend
- Developers who use GitHub Copilot every day and want more accurate, useful results.
- Tech leads and engineering managers rolling out Copilot to a team and setting the policies around it.
- DevOps engineers who automate work with the Copilot CLI and agent features.
- App makers and technology managers who need to understand what Copilot does with code and data before they approve it.
Prerequisites
- There are no formal prerequisites for the GH-300 exam or for this course.
- GitHub recommends reviewing the related Microsoft Learn modules before the exam. We cover the same skills in class.
- You should know GitHub fundamentals and have experience with at least one programming language.
- Access to GitHub Copilot will help you practice between sessions.
Pathway Map
The GitHub Copilot course follows the six GH-300 skill domains.
Each module maps to an official exam domain and its published weight, from responsible AI to the settings that protect your code.
Course Content
- Enabling Copilot in the IDE and using inline suggestions, chat and agent mode.
- Installing and using the Copilot CLI to run sessions, generate scripts and manage files.
- Agent Mode, Copilot Edits, MCP, agent sessions, sub-agents, code review, Spaces, Spark and pull request summaries.
- Organization-wide policies, Copilot Code Review policies, audit log events and managing subscriptions with the REST API.
- How data is used, where it flows and what is shared.
- How Copilot processes input and builds a prompt.
- Proxy filtering and post-processing of suggestions.
- The code suggestion lifecycle and the limits of LLMs and Copilot.
- Prompt structure and how Copilot decides what context to use.
- Zero-shot and few-shot prompting.
- Best practices for writing prompts that get useful answers.
- The prompt process flow and how chat history is used.
- Code generation, refactoring and documentation with Copilot.
- Learning faster, cutting context switching, generating sample data and modernizing legacy code.
- Writing unit and integration tests, finding edge cases and writing assertions.
- Getting suggestions for security improvements and performance fixes.
- Setting content exclusions and editor settings.
- Ownership of Copilot output and its limitations.
- Turning on filtering for suggestions that match public code.
- Fixing problems with suggestions and content exclusions.
Course Features
Built for practical GitHub Copilot training and GH-300 exam prep.
Interactive Learning
Participate in training sessions, discussions, and hands-on labs with experienced instructors.
Comprehensive Study Materials
Access extensive resources, including e-books, video lectures, and practice exams.
Practical Scenarios
Engage in real-world exercises and case studies to apply GitHub Copilot concepts.
Certification Preparation
Receive guidance and tips to successfully pass the GitHub Copilot exam.
Certification Exam
Prepare for the official GitHub Copilot exam.
GH-300 Exam Readiness
Accumentum’s GitHub Copilot course follows the official GH-300 skills outline and prepares you for every domain on the exam.
After the course you will be ready to take the official GitHub Copilot (GH-300) exam. GitHub describes it as an exam that evaluates your skill using Copilot across programming languages to make software development workflows more efficient.
The exam is intermediate level and runs 100 minutes. You can take it at a Pearson VUE testing center or online, in English, Portuguese, Spanish, Korean or Japanese. A score of 700 or higher is required to pass.
The certification is valid for 2 years. GitHub is moving to Microsoft’s recertification process, which will let you keep your certification current without retaking the full exam.
Skills Measured
What Microsoft says GH-300 measures.
Microsoft publishes the skills measured for Exam GH-300 as of August 7, 2026. Here are all 6 domains, 14 skill groups and 41 tasks in Microsoft's own wording. Our course maps a lesson or lab to each one.
Understand responsible AI principles
Part of Use GitHub Copilot responsibly (15 to 20%)
- Describe risks and limitations of Generative AI tools
- Describe ethical and responsible AI usage
- Identify potential harms and mitigation strategies of AI usage
Validate and operate AI tools
Part of Use GitHub Copilot responsibly (15 to 20%)
- Explain the need to validate AI output
- Identify how to operate GitHub Copilot responsibly
Use GitHub Copilot in the IDE
Part of Use GitHub Copilot features (25 to 30%)
- Enable Copilot in the IDE
- Trigger Copilot through inline suggestions, chat, CLI, and agent mode
- Configure content exclusions for specific files or repositories (app knowledge)
Use GitHub Copilot CLI
Part of Use GitHub Copilot features (25 to 30%)
- Define GitHub Copilot CLI and how it benefits developers
- Identify the steps for installing GitHub Copilot CLI
- Describe key GitHub Copilot CLI features and commands
- Use GitHub Copilot CLI interactively and in sessions
- Generate scripts and manage files with GitHub Copilot CLI
Use GitHub Copilot features and capabilities
Part of Use GitHub Copilot features (25 to 30%)
- Use Agent Mode, Copilot Edits, and MCP for enhanced development and workflows, manage Agent Sessions and delegate tasks to Sub‑Agents for optimized context usage
- Use Copilot for code review and coding assistance
- Utilize Spaces, Spark, Pull Request summaries, and customizable review standards via instructions files
- Understand the limits, options, feedback, and commands of GitHub Copilot Chat, include prompt file reuse for consistent responses
Manage organization-wide settings and policies
Part of Use GitHub Copilot features (25 to 30%)
- Configure organization-wide policy management, enable Copilot Code Review policies and manage feature availability across IDEs and github.com
- Utilize audit log events
- Manage subscriptions using the REST API
Describe data handling and flow
Part of Understand GitHub Copilot data and architecture (10 to 15%)
- Explain data usage, flow, and sharing
- Describe input processing and prompt building
- Explain proxy filtering and post-processing
Understand lifecycle and limitations
Part of Understand GitHub Copilot data and architecture (10 to 15%)
- Visualize code suggestion lifecycle
- Describe limitations of LLMs and Copilot
Craft effective prompts
Part of Apply prompt engineering and context crafting (10 to 15%)
- Describe prompt structure and context
- Understand how context is determined
- Use zero-shot and few-shot prompting
- Apply best practices for prompt crafting
Engineer prompts for performance
Part of Apply prompt engineering and context crafting (10 to 15%)
- Explain prompt engineering principles
- Describe prompt process flow and chat history usage
Enhance productivity and code quality
Part of Improve developer productivity with GitHub Copilot (10 to 15%)
- Use Copilot for code generation, refactoring, and documentation
- Accelerate learning and reduce context switching
- Generate sample data and modernize legacy code
Support testing and security
Part of Improve developer productivity with GitHub Copilot (10 to 15%)
- Generate unit and integration tests
- Identify edge cases and write assertions
- Suggest security improvements and performance optimizations
Manage privacy settings and exclusions
Part of Configure privacy, content exclusions, and safeguards (10 to 15%)
- Configure content exclusions and editor settings
- Describe ownership and limitations of outputs
Apply safeguards and troubleshoot
Part of Configure privacy, content exclusions, and safeguards (10 to 15%)
- Enable suggestions matching public code filtering
- Resolve issues with suggestions and content exclusions
Who It Is For
The GH-300 candidate profile.
Here's how Microsoft describes the person this exam is built for. Candidates for this exam should possess expertise in using GitHub Copilot to improve software development productivity, quality, and security. This includes responsible AI use, prompt engineering, Copilot features across various plans, and privacy safeguards. Candidates should also be familiar with GitHub fundamentals and have experience with one or more programming languages.
Study Plan
A practical path to GH-300.
We open with Use GitHub Copilot responsibly, which Microsoft weights at 15 to 20%. Its skill groups are "Understand responsible AI principles" and "Validate and operate AI tools".
Next comes Use GitHub Copilot features, worth 25 to 30% of the exam. Microsoft breaks it into "Use GitHub Copilot in the IDE", "Use GitHub Copilot CLI", "Use GitHub Copilot features and capabilities" and "Manage organization-wide settings and policies".
After that we move to Understand GitHub Copilot data and architecture, which counts for 10 to 15%. You'll see it split into "Describe data handling and flow" and "Understand lifecycle and limitations".
Then we take on Apply prompt engineering and context crafting, at 10 to 15% of your score. Inside it are "Craft effective prompts" and "Engineer prompts for performance".
We follow with Improve developer productivity with GitHub Copilot, which Microsoft weights at 10 to 15%. The groups here are "Enhance productivity and code quality" and "Support testing and security".
We close with Configure privacy, content exclusions, and safeguards, worth 10 to 15% of the exam. It holds "Manage privacy settings and exclusions" and "Apply safeguards and troubleshoot".
Use GitHub Copilot features carries the most weight, so it gets the most lab time. In the last week you take Microsoft's free practice assessment, review whatever it flags and try the exam sandbox so the interface holds no surprises.
Exam Policies
How Microsoft runs the GH-300 exam.
GH-300 leads to the GitHub Copilot certification. Microsoft requires a score of 700 or greater to pass, and you get 100 minutes to complete the exam. It's proctored and may include interactive components.
The exam is offered in English, Spanish, Portuguese (Brazil), Korean and Japanese. If it isn't available in your preferred language, Microsoft lets you request an extra 30 minutes. You can also request accommodations if you use assistive devices or need extra time.
If you don't pass, you can retake the exam 24 hours after your first attempt. Waits for later retakes vary under Microsoft's retake policy. Exam price depends on the country or region where the exam is proctored.
Microsoft notes that the bullets under each skill show how the skill is assessed, and related topics may also appear. Most questions cover generally available features, though Preview features can show up if they're commonly used.
GitHub certifications are valid for 2 years. GitHub is moving to Microsoft's recertification process so you can maintain a certification without retaking the full exam, and certifications that expire before that process is available are extended by 6 months.
See the GitHub Copilot certification page on Microsoft Learn.
Career Outlook
Where GH-300 can take you.
The U.S. Bureau of Labor Statistics reports that the median annual wage for software developers, quality assurance analysts and testers was $134,040 in May 2025. Treat it as a reference point and not a promise. Location, experience and the employer drive what any one person earns. Source: BLS Occupational Outlook Handbook.
Funding and PathPay
Ways to pay for GH-300 training.
Paying on your own? GH-300 prep is eligible for PathPay, our monthly payment plan. Terms of 3, 4 and 6 months carry no added fee. 9, 12 and 18 month terms add 5%, 10% and 15%. Course access opens when your first payment clears.
Our funding page lists every other way to pay, and you can always talk with us or email info@accumentum.net before you enroll.
Frequently Asked Questions
Answers to common questions about Accumentum’s GitHub Copilot course, the GH-300 exam, eligibility, delivery and payment.
It shows you can use GitHub Copilot to improve how you build software, including responsible AI use, prompt engineering, Copilot features across plans and privacy safeguards. The exam code is GH-300.
Developers and tech leads who use Copilot or are rolling it out to a team. App makers, DevOps engineers and technology managers also fit the official audience for the exam.
There are no formal prerequisites. You should know GitHub fundamentals and have experience with at least one programming language. GitHub recommends reviewing the related Microsoft Learn modules first.
Six domains: use GitHub Copilot responsibly (15 to 20%), use GitHub Copilot features (25 to 30%), Copilot data and architecture (10 to 15%), prompt engineering and context crafting (10 to 15%), developer productivity (10 to 15%), and privacy, content exclusions and safeguards (10 to 15%).
The exam runs 100 minutes. You can take it at a Pearson VUE testing center or online. It is offered in English, Portuguese, Spanish, Korean and Japanese.
You need a score of 700 or higher.
It is valid for 2 years. GitHub is moving to Microsoft’s recertification process, which will let you renew without retaking the full exam.
The course is delivered live online by an instructor, with hands-on practice in GitHub between sessions.
Yes. PathPay lets you pay for your training over time instead of all at once. You can enroll through PathPay from this page or contact us with any questions.
Microsoft lists these domains:
- Use GitHub Copilot responsibly, 15 to 20%
- Use GitHub Copilot features, 25 to 30%
- Understand GitHub Copilot data and architecture, 10 to 15%
- Apply prompt engineering and context crafting, 10 to 15%
- Improve developer productivity with GitHub Copilot, 10 to 15%
- Configure privacy, content exclusions, and safeguards, 10 to 15%
Use GitHub Copilot features is the largest at 25 to 30%. We give it the most lab time.
You can retake it 24 hours after your first attempt. Later retakes have longer waits under Microsoft's retake policy.
Yes. Microsoft offers a free practice assessment, plus an exam sandbox that shows you the exam interface.
Enrollment
Enroll in the GitHub Copilot (GH-300) Certification Training Course with Accumentum.
Enroll in the GitHub Copilot (GH-300) Certification Training Course with Accumentum to learn how to use Copilot well and roll it out safely. You will cover every GH-300 domain, from responsible AI and Copilot features to prompt engineering, data handling and privacy settings.
When you finish, you will be ready to sit the GitHub Copilot exam and help your team get real value from the tool. For upcoming class dates and to save your seat, use the registration page linked below.
Get more out of GitHub Copilot with GH-300 training.
Prepare for the GitHub Copilot (GH-300) exam, write better prompts, and roll Copilot out to your team with the right guardrails.