Free Microsoft GH-300 Exam Questions

Question 1

You are a developer working for a company that handles sensitive data and has strict policies regarding code generated by external tools. Your manager is concerned about the way GitHub Copilot handles data, specifically whether it accesses or uses the code written by developers in sensitive projects. You need to provide a clear explanation of how GitHub Copilot handles user data and whether it presents any security or compliance risks for your company's projects. Which of the following best describes how GitHub Copilot handles user data during code suggestions?

A : GitHub Copilot only generates suggestions based on publicly available open-source code repositories and does not access your private code.

B : GitHub Copilot uses and stores your code to improve its AI model for other users.

C : GitHub Copilot may use the code you are writing in real-time to generate suggestions, but it does not store or use that code to train its AI model.

D : GitHub Copilot requires explicit user consent before accessing any files within your repository to provide code suggestions.

Answer: C

Question 2

You are working on a Python project in your integrated development environment (IDE), and you activate GitHub Copilot to assist you with code suggestions. As you begin typing, Copilot provides a series of code snippets. You want to understand how GitHub Copilot generates these suggestions and handles data at each step. Which of the following best describes the lifecycle of how GitHub Copilot processes your input and provides a code suggestion?

A : GitHub Copilot retrieves the code from a pre-trained local database on your machine, matches it to similar code snippets from your previous projects, and presents suggestions based on your coding style.

B : GitHub Copilot transmits your code to an AI model hosted in the cloud, which analyzes both your code and GitHub repositories you’ve starred, presenting suggestions tailored to these repositories.

C : GitHub Copilot sends your code and surrounding context to a large language model hosted on a remote server, which processes it through machine learning models trained on public GitHub repositories and other sources, returning contextually relevant code suggestions.

D : GitHub Copilot sends your code to a remote server, which compares it with existing open-source repositories hosted on GitHub, and generates suggestions by copy-pasting code from the most popular projects.

Answer: C

Question 3

Which of the following best represents a best practice for prompting GitHub Copilot Chat to improve code accuracy and relevance?

A : Providing context and comments to Copilot Chat about the desired output for specific functions.

B : Asking for the best solution without providing details about the intended functionality.

C : Expecting Copilot Chat to identify and solve all logical errors within the code independently.

D : Requesting Copilot Chat to override all existing code with its suggested changes automatically.

Answer: A

Question 4

You are a developer who frequently works from the command line. You want to install GitHub Copilot in the CLI to leverage its auto-completion capabilities while working on various projects. What are the correct steps to install GitHub Copilot in the CLI?

A : Use Homebrew to install GitHub Copilot by running brew install github-copilot, then authenticate with your GitHub credentials.

B : Clone the GitHub Copilot repository, navigate to the cli folder, and run the make install command.

C : Install the GitHub Copilot CLI via NPM, run the copilot setup command, and authenticate using a personal access token.

D : Install GitHub Copilot CLI through pip by running pip install github-copilot-cli, then configure it with the copilot-cli configure command.

Answer: C

Question 5

You are using GitHub Copilot to help with a mathematical algorithm that requires precise calculations. While Copilot is excellent at generating code snippets, you're curious about its ability to provide reasoning and perform precise calculations. Which of the following best describes GitHub Copilot’s capabilities and limitations in this scenario?

A : GitHub Copilot can perform complex calculations accurately by leveraging its deep learning model, which is optimized for mathematical computations.

B : GitHub Copilot can process and reason through mathematical proofs, ensuring that the code generated is logically sound and mathematically correct.

C : GitHub Copilot can generate code for calculations, but it relies on the logic you provide in the prompt and does not inherently understand or guarantee the accuracy of the calculations.

D : GitHub Copilot is specifically designed to handle mathematical reasoning and calculations and can replace tools like Wolfram Alpha or scientific calculators.

Answer: C