GH-300 Microsoft GitHub Copilot Exam Free Practice Exam Questions (2026 Updated)

Utilize to interpret developer ' s thoughts and intentions without any code or comments.

Engage with chat participants such as @workspace to incorporate collaborative context into the responses.

Access developer ' s previous projects and code repositories to understand their coding style without explicit permission.

Utilize chat variables like *file to anchor the conversation within the specific context of the files or editors in use.

GitHub Copilot can fix syntax errors without user input.

GitHub Copilot can automatically rewrite code to follow best practices.

GitHub Copilot can suggest refactoring improvements for better code quality.

GitHub Copilot can remove unnecessary files from the project directory.

Translates code into a more performant language.

Enhances the performance of the selected code by analyzing its runtime complexity.

Automatically formats the code according to the selected style guide.

Summarizes your documentation into more maintainable and readable formats.

Responses are faster to produce and appear sooner

Responses use practices and patterns in your repositories

Responses use the organization ' s LLM engine

Responses are guaranteed to be correct

Monthly as a subscription

Annually as a subscription

Monthly, as a metered service based on actual consumption

Free (not billed) for all open source projects

Code suggestions

Chat

Knowledge Base

Pull Request Diff Analysis

Keep the prompt as short as possible, using single words or brief phrases.

Write the prompt in natural language without any programming language.

Avoid mentioning the programming language to allow for more flexible suggestions.

Provide examples of expected input and output within the prompt.

Only giving GitHub Copilot a question as a prompt and no examples

Giving GitHub Copilot examples of the problem you want to solve

Telling GitHub Copilot it needs to show only the correct answer

Giving GitHub Copilot examples of the algorithm and outcome you want to use

Giving as little context to GitHub Copilot as possible

Create a technical requirement specification from the business requirement documentation

Explain a legacy COBOL code and translate the code to another language like Python.

Creation of a unit test scenario for newly developed Python code

Creation of end-to-end performance testing scenarios for a web application

It filters out irrelevant information from the user ' s input prompt.

It enriches the input prompt with additional context before passing it to the language model.

It directly generates a response based on the user ' s input prompt.

It formats the output response before presenting it to the user.

Focusing on accessibility will ensure fairness.

Focusing on collecting large datasets for training will ensure fairness.

Regularly monitoring the AI tool ' s performance will ensure fairness in its outputs.

Training AI data and algorithms to be free from biases will ensure fairness.

GitHub Copilot Individuals

GitHub Copilot Business

GitHub Copilot Enterprise

GitHub Copilot Codespace

The API can generate detailed reports on code quality improvements made by GitHub Copilot.

The API can track the acceptance rate of code suggestions accepted and used in the organization.

The API can refactor your code to improve productivity.

The API can provide feedback on coding style and standards compliance.

The API can provide Copilot Chat specific suggestions acceptance metrics.

All repos are indexed

Indexing is static

It is an Enterprise feature

All file types are indexed

Clearly defining the problem or task

Including personal information in the code comments

Using meaningful variable names

Providing examples of desired output

Use a .gitignore file to exclude irrelevant files

By automatically generating detailed requirements documents.

By providing templates and code snippets that help in documenting requirements.

By identifying and fixing potential requirement conflicts when using /help.

By managing stakeholder communication and meetings.

When the user prompts with @workspace.

When the repository-level settings allow overrides by the user.

If the contents of an excluded file are referenced in code that is not excluded, for example function calls.

If the content exclusion was configured at the enterprise level, and is overwritten at the organization level.

Navigate to the Security tab in the organization ' s GitHub settings

Navigate to the Insights tab in the repository settings

Use the Audit log section in the organization ' s GitHub settings

Use the Code tab in the GitHub repository

By using chat history to offer personalized code snippets based on previous prompts.

By logging chat history to monitor user activity and ensure compliance with coding standards.

By analyzing past chat interactions to identify common programming patterns and errors.

By sharing chat history with third-party services to improve integration and functionality.