Free Preparation Discussions
MENU
Microsoft GH-300 Exam Questions
- Topic 1: Responsible :This section of the exam measures skills of AI Ethics Officers and Risk Managers and covers the responsible and ethical usage of AI technologies. It explains the risks and limitations associated with generative AI tools, including biases in training data and the need to validate AI outputs. Candidates learn how to operate AI responsibly by identifying potential harms such as bias, fairness, privacy concerns, and mitigating these harms by applying ethical AI principles.
- Topic 2: GitHub Copilot Plans and Feature: This domain targets Product Managers and DevOps Engineers and focuses on understanding the various GitHub Copilot subscription plans like Individual, Business, and Enterprise, including distinctions and management features. It covers how Copilot is integrated into IDEs, different triggering methods for code suggestions, organizational policy management, subscription administration via API, and effective use of Copilot Chat and Knowledge Bases. Candidates also learn about CLI usage and configuration.
- Topic 3: How GitHub Copilot Works and Handles Data: Designed for Machine Learning Engineers and Data Privacy Specialists, this section covers the data lifecycle and processing behind Copilot’s code suggestions. It explains how context is gathered, prompts constructed, responses generated, and post-processed through proxy services. Candidates understand Copilot’s data policies, handling of inputs, and limitations such as context window size and data age influencing suggestion relevance.
- Topic 4: Domain 4: Prompt Crafting and Prompt Engineering This section measures skills of Software Developers and AI Interaction Designers in effectively crafting prompts to optimize Copilot’s output. It reviews foundational concepts such as prompt components, the role of language in prompting, zero-shot vs. few-shot prompting, and how chat history influences responses. Best practices and engineering principles for prompt design and training methods are also covered.
- Topic 5: Developer Use Cases for AI: Targeting Software Engineers and Technical Leads, this domain elaborates on how AI improves developer productivity across common tasks like learning new languages, translation, documentation, debugging, data science, and refactoring. It discusses Copilot’s support in software development lifecycle management and highlights its limitations. Use of the productivity API to track Copilot’s impact is also included.
- Topic 6: Domain 6: Testing with GitHub Copilot: This section measures abilities of QA Engineers and Test Automation Specialists to use Copilot for test generation, including unit and integration tests. It explains how Copilot can identify edge cases and assist in writing assertions. The domain also covers different Copilot subscription SKUs, privacy considerations, organizational code suggestion settings, and configuration files related to Copilot.
- Topic 7: Privacy Fundamentals and Context Exclusions: This domain focuses on Security Engineers and Compliance Officers and addresses improving code quality with Copilot’s test suggestions and security optimizations. It covers identification of security vulnerabilities, performance enhancements, and privacy features like content exclusions at repository and organization levels with explanation of their limitations. Candidates learn about safeguarding mechanisms such as duplication detection, contractual protections, security checks, and troubleshooting guide for common Copilot issues including context exclusions and suggestion gaps.
Free Microsoft GH-300 Exam Actual Questions
Note: Premium Questions for GH-300 were last updated On Sep. 09, 2025 (see below)
What are two techniques that can be used to improve prompts to GitHub Copilot? (Select two.)
Improving prompts involves providing specific success criteria and including links to supporting documentation to give GitHub Copilot more context and direction.
What are the potential risks associated with relying heavily on code generated from GitHub Copilot? (Each correct answer presents part of the solution. Choose two.)
Heavy reliance on GitHub Copilot can introduce security vulnerabilities if the generated code contains known exploits. Additionally, Copilot's suggestions may not always align with best practices or the latest standards, requiring careful review and validation.
Which Copilot Individual features are available when using a supported extension for Visual Studio, VS Code, or JetBrains IDEs? (Each correct answer presents part of the solution. Choose two.)
GitHub Copilot Individual provides code suggestions and chat features when used with supported IDE extensions like Visual Studio, VS Code, and JetBrains IDEs.
Why is code reviewing still necessary when using GitHub Copilot to write tests?
Code review is necessary because GitHub Copilot's generated test cases might not cover all possible scenarios, especially edge cases and complex interactions.
What is a benefit of using custom models in GitHub Copilot?
Custom models in GitHub Copilot allow the tool to learn from the specific code patterns and practices within your repositories. This results in suggestions that are more aligned with your organization's coding standards and conventions, improving the relevance and accuracy of the generated code.
- Select Question Types you want
- Set your Desired Pass Percentage
- Allocate Time (Hours : Minutes)
- Create Multiple Practice tests with Limited Questions
- Customer Support
Kate
10 hours agoSusy
10 hours agoHelene
10 hours ago