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Microsoft GH-300 Exam Syllabus Topics:

Topic	Details
Topic 1	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 2	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 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	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 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.

Reference: https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/GH-300

Microsoft GitHub Copilot Sample Questions:

Question #1

A company is currently storing code in Bitbucket and would like to use GitHub Copilot. Which GitHub Copilot plan will be most cost effective to allow them to manage users with their Identity Provider (e.g. Okta)?

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

Reveal Solution Discussion 0

Correct Answer: B 🗳️