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AZ-700· SC-100· SC-200· SC-300· SC-401· SC-500· SC-730· AI-103· AI-300· GH-300· AB-100
GH-300

GitHub Copilot

GitHub Copilot Certification (GH-300)
PS academy:/courses> Get-Certification -Id GH-300 | Select-Object -ExpandProperty Overview
40–60
Questions
~100 min
Duration
700
Passing score / 1000
6
Domains
Associate
Level
PSacademy:/courses/gh-300> Get-DomainWeights | Format-Chart
Use GitHub Copilot responsibly
15–20% of exam
Use GitHub Copilot features
25–30% of exam
Understand GitHub Copilot data and architecture
10–15% of exam
Apply prompt engineering and context crafting
10–15% of exam
Improve developer productivity
10–15% of exam
Configure privacy fundamentals and context exclusions
10–15% of exam
PSacademy:/courses/gh-300> Get-LearningModules -Cert GH-300
MOD 01

Responsible Copilot Use

  • Generative AI limitations, risks, and potential harms
  • Human review, validation, and accountability for generated code
  • Bias, fairness, and transparency in AI-assisted development
  • Mitigating insecure or incorrect suggestions before merge
  • Responsible use across the software development lifecycle
MOD 02

Copilot Features and Environments

  • IDE inline suggestions, Copilot Chat, Edits, and agent mode
  • Slash commands, chat participants, and chat variables
  • Copilot on GitHub.com, Copilot CLI, and Copilot code review
  • Copilot cloud agent working on assigned issues and pull requests
  • Plans, organization policies, seat management, and audit events
  • Custom instructions, prompt files, and MCP servers
MOD 03

Data Flow and Architecture

  • Context gathering from open files, neighbouring tabs, and repository
  • Prompt processing, proxy filtering, and post-processing
  • Suggestion lifecycle and large language model limitations
  • Data retention for prompts and suggestions by plan
  • Trust boundaries and data sharing controls
MOD 04

Prompt Engineering and Context

  • Task, context, constraints, examples, and acceptance criteria
  • Zero-shot and few-shot prompting patterns
  • Iterative refinement and breaking down complex tasks
  • Chat history, #file / #selection / #codebase context
  • Reusable prompt files and repository instructions
MOD 05

Productivity, Testing, and Security

  • Code generation, refactoring, documentation, and modernization
  • Unit and integration tests, edge cases, and assertions
  • Security review with code scanning, secret scanning, and Dependabot
  • Public code matching filter and code referencing
  • Measuring adoption and outcomes with the Copilot metrics API
MOD 06

Applied Developer Scenarios

  • Responsible rollout for regulated engineering teams
  • Content exclusions and their limitations
  • Organization-wide policy, instructions, and enablement
  • Real-world productivity and quality measurement
  • Balancing autonomy of agents with review gates

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