GitHub Exams

From Code Host to Automation Engine

In 2007, GitHub launched as a simple Git repository host. As of 2025, it operates as the primary development platform for over 150 million registered developers worldwide. Microsoft acquired the company for $7.5 billion in 2018, accelerating its transition from a pure version control system into an automation and artificial intelligence hub.

As the platform grew more complex, companies needed a way to verify that developers actually understood how to use its advanced features. In January 2024, GitHub opened its previously internal certification program to the public. Instead of testing basic Git commands, the modern credentialing paths focus on tools that reduce manual labor. They validate your ability to build continuous integration pipelines and use AI pair programming.

The Certification Landscape

GitHub structures its credentialing program around specific technical competencies. There is no rigid, multi-year progression track. You do not need to pass a foundational exam before attempting a specialized one. Each exam costs $99 and takes place in a proctored environment. They test your practical ability to configure, secure, and operate enterprise-grade tools.

Automating Workflows with GitHub Actions

Continuous integration and continuous deployment (CI/CD) dictate how fast a software team can ship code. The GitHub Actions certification proves you can design and maintain these automated pipelines. Millions of workflows execute on GitHub Actions every day, making this a frequent requirement for infrastructure teams.

If your organization uses GitHub Enterprise, this credential signals that you understand how to move code from a pull request to production safely. The exam runs for 120 minutes and contains approximately 75 questions.

The test breaks down into four specific domains. Forty percent of the exam focuses on authoring and maintaining workflows. You must know how to trigger events, run jobs concurrently, and manage matrix builds. Another 25 percent covers authoring custom actions. This requires you to understand Docker container actions, JavaScript actions, and composite actions. The remaining sections test your ability to consume existing workflows securely and manage GitHub Actions at the enterprise level. This includes configuring self-hosted runners and enforcing repository policies.

GitHub Actions uses YAML syntax to define workflows. The exam expects you to read raw YAML snippets and spot indentation errors, missing keywords, or incorrect event triggers. You will also need to understand how to use GitHub's default tokens for authenticating within a workflow run, and when to configure OpenID Connect (OIDC) for deploying to external cloud providers.

The test does not just ask what a command does. It presents real-world scenarios where a pipeline fails and asks you to identify the syntax error or permission issue. Candidates should have hands-on experience managing workflow secrets and environment variables before booking the test.

AI-Assisted Development with GitHub Copilot

Artificial intelligence is changing how engineers write software. The GitHub Copilot certification (exam code GH-300) validates your ability to use GitHub's AI pair programmer effectively.

Many developers assume Copilot is just an advanced autocomplete tool. This exam corrects that assumption. It tests your proficiency in prompt engineering, specifically the 4S framework: being Specific, providing Structure, asking for Step-by-step guidance, and offering Starter code.

Copilot integrates directly into your Integrated Development Environment (IDE). The GH-300 exam expects you to know how to interact with the Copilot chat panel, inline suggestions, and slash commands within editors like Visual Studio Code. A crucial part of the test involves Responsible AI principles, which make up 7 percent of the score. You must recognize the ethical implications of AI-generated code, including copyright concerns and bias mitigation.

You will face scenario-based questions that test how Copilot handles data and privacy. The exam allocates 15 percent of its questions to context exclusions and privacy fundamentals. Another 15 percent covers how the underlying model processes your code. Companies want to know that if they give you an AI coding assistant, you will not inadvertently leak proprietary code or accept insecure suggestions.

You must also demonstrate how to use Copilot for specific developer use cases (14 percent of the exam) and testing (9 percent). This includes writing unit tests, debugging legacy code, and generating documentation. You must score at least 700 out of 1000 to pass this 100-minute exam.

Market Position and Hiring Value

These credentials carry distinct weight depending on your role.

For DevOps engineers and release managers, the GitHub Actions credential holds immediate practical value. Hiring managers looking to migrate from Jenkins or GitLab CI to GitHub Actions actively seek professionals who understand the specific syntax and security boundaries of the platform.

For software engineers, the GitHub Copilot certification serves a different purpose. It shows engineering directors that you know how to integrate AI into your daily routine to increase velocity. As companies invest heavily in Copilot licenses for their engineering teams, they want assurance that their developers know how to extract actual return on that investment.

In early 2025, developers created over 70,000 new public generative AI projects on GitHub. As organizations shift their budgets toward AI-assisted development and automated CI/CD, the expectation for engineers changes. Employers now expect you to manage the entire lifecycle of that code - from the first AI-generated prompt to the final automated deployment to production.