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Microsoft GH-300 Exam Overview:

Certification Vendor:	Microsoft
Exam Name:	GitHub Copilot
Exam Number:	GH-300
Passing Score:	700 / 1000
Real Exam Qty:	60–65
Exam Price:	$99 USD
Exam Format:	Multiple-choice, Proctored, Scenario-based
Available Languages:	Portuguese (Brazil), Arabic (Saudi Arabia), German, Japanese, Spanish, French, Chinese (Simplified), English, Korean
Exam Duration:	100 minutes
Certificate Validity Period:	1 year
Recommended Training:	Microsoft Learn: GitHub Copilot Learning Path
Exam Registration:	Pearson VUE Registration Microsoft Learn Exam Details
Sample Questions:	Microsoft GH-300 Sample Questions
Exam Way:	Online proctored or onsite at Pearson VUE test centers
Pre Condition:	Basic familiarity with GitHub, software development workflows, and at least one programming language; no formal prerequisites required
Official Syllabus URL:	https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/GH-300

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Microsoft GH-300 Exam Syllabus Topics:

Topic	Details
Topic 1	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 2	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 3	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 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.
Topic 5	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.

Microsoft GitHub Copilot Sample Questions (Q126-Q131):

NEW QUESTION # 126
How does GitHub Copilot Chat ensure that a function works correctly?

A. By automatically writing all the tests for the function.
B. By executing the test cases to validate the correctness of the code.
C. By suggesting assertions based on the code's context and semantics.
D. By writing the implementation code for the function.

Answer: C

Explanation:
GitHub Copilot Chat can suggest assertions based on the code's context and semantics to help developers verify the correctness of their functions. These assertions serve as checks that the function behaves as expected under various conditions.

NEW QUESTION # 127
Which principle emphasizes that AI systems should be understandable and provide clear information on how they work?

A. Transparency
B. Inclusiveness
C. Fairness
D. Accountability

Answer: A

Explanation:
The principle of transparency emphasizes that AI systems should be understandable and provide clear information about their operations. This ensures that users can understand how the AI arrives at its decisions and suggestions.

NEW QUESTION # 128
How does the /tests slash command assist developers?

A. Integrates with external testing frameworks.
B. Constructs detailed test documentation.
C. Executes test cases to find issues with the code.
D. Creates unit tests for the selected code.

Answer: D

Explanation:
The /tests slash command in GitHub Copilot Chat creates unit tests for the selected code, helping developers ensure the functionality and reliability of their code.

NEW QUESTION # 129
An independent contractor develops applications for a variety of different customers. Assuming no concerns from their customers, which GitHub Copilot plan is best suited?

A. GitHub Copilot Enterprise
B. GitHub Copilot Business
C. GitHub Copilot Teams
D. GitHub Copilot Individual
E. GitHub Copilot Business for non-GHE Customers

Answer: D

Explanation:
For an independent contractor, GitHub Copilot Individual is the most suitable and cost-effective plan.

NEW QUESTION # 130
What types of prompts or code snippets might be flagged by the GitHub Copilot toxicity filter? (Each correct answer presents part of the solution. Choose two.)

A. Code comments containing strong opinions or criticisms
B. Sexually suggestive or explicit content
C. Code that contains logical errors or produces unexpected results
D. Hate speech or discriminatory language (e.g., racial slurs, offensive stereotypes)

Answer: B,D

Explanation:
GitHub Copilot includes a toxicity filter to prevent the generation of harmful or inappropriate content. This filter flags prompts or code snippets that contain hate speech, discriminatory language, or sexually suggestive or explicit content. This ensures a safe and respectful coding environment.
Reference: GitHub Copilot documentation on safety and content filtering.

NEW QUESTION # 131
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