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Microsoft GH-300 Exam Syllabus Topics:

Topic	Details
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	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 4	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.

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Microsoft GitHub Copilot Sample Questions (Q54-Q59):

NEW QUESTION # 54
How can the concept of fairness be integrated into the process of operating an AI tool?

A. Training AI data and algorithms to be free from biases will ensure fairness.
B. Regularly monitoring the AI tool's performance will ensure fairness in its outputs.
C. Focusing on accessibility will ensure fairness.
D. Focusing on collecting large datasets for training will ensure fairness.

Answer: A

Explanation:
Fairness in AI tools is achieved by training the data and algorithms to be free from biases. This ensures that the tool treats all users equitably and avoids discriminatory outcomes.
Reference: Microsoft's AI principles and fairness guidelines.

NEW QUESTION # 55
How is GitHub Copilot Individual billed? (Each correct answer presents part of the solution. Choose two.)

A. Monthly, as a metered service based on actual consumption
B. Monthly as a subscription
C. Free (not billed) for all open source projects
D. Annually as a subscription

Answer: B,D

Explanation:
GitHub Copilot Individual is billed as a monthly or annual subscription.
Reference: GitHub Copilot Individual pricing.

NEW QUESTION # 56
When using an IDE with a supported GitHub Copilot plug-in, which Chat features can be accessed from within the IDE? (Each correct answer presents part of the solution. Choose two.)

A. Generate unit tests
B. Explain code and suggest improvements
C. Find out about releases and commits
D. Plan coding tasks

Answer: A,B

Explanation:
Exact extracts:
* "In supported IDEs, you can ask Copilot Chat to explain code or suggest improvements." References: GitHub Copilot Chat IDE integration documentation.

NEW QUESTION # 57
You have a GitHub repository named Repo1 that has GitHub Copilot enabled.
The developers at your company use Repo1 in Microsoft Visual Studio Code.
You need to identify potentially unoriginal suggestions and prevent secrets from being committed to Repo1.
The solution must ensure that the developers can use inline GitHub Copilot suggestions in Visual Studio Code.
Which two actions should you perform? Each correct answer presents part of the solution.

A. Disable inline GitHub Copilot suggestions in the IDE.
B. Add repository custom instructions for secure coding, or create a custom push policy and configure a code check run.
C. Enable code referencing for GitHub Copilot completions.
D. Enable push protection for secret scanning on Repo1.

Answer: C,D

Explanation:
Two separate GitHub features satisfy the security requirements. Push protection is part of secret scanning and blocks supported secrets before they are pushed to a repository, helping prevent credentials from being committed. GitHub Copilot code referencing addresses potentially unoriginal suggestions: when public-code matches are allowed, accepted inline suggestions that match public GitHub code can be logged with source URLs and license information so developers can review the origin. Disabling inline suggestions would violate the requirement that developers continue using Copilot completions. Repository custom instructions may influence generated code, but they do not replace secret scanning or public-code matching. Therefore, enabling push protection together with Copilot code referencing is the correct combination.

NEW QUESTION # 58
What are the potential limitations of GitHub Copilot Chat? (Each correct answer presents part of the solution. Choose two.)

A. Ability to handle complex code structures
B. No biases in code suggestions
C. Limited training data
D. Extensive support for all programming languages

Answer: C,D

Explanation:
GitHub Copilot Chat has limitations such as limited training data, which can affect the accuracy of its suggestions, and it does not provide extensive support for all programming languages.

NEW QUESTION # 59
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