GitHub Copilot Certification (GH-300): Complete Preparation
About this course
“This course contains the use of artificial intelligence.”This course maps every skill area on the official exam blueprint to focused, scenario-based lectures. No hype, no filler — just honest, practical preparation built by an architect who uses Copilot in production every day.What you will learn: How GitHub Copilot works under the hood — LLMs, the request pipeline, content filtering, and telemetry Code completions, Chat, slash commands, agents, and context variables across VS Code, JetBrains, and other IDEs Prompt engineering patterns — zero-shot, few-shot, and instructional techniques that produce better suggestions Code generation, refactoring, documentation, and DevOps use cases (CI/CD, Infrastructure as Code) Test generation strategies — unit, integration, and end-to-end testing with Copilot Privacy fundamentals — content exclusions, context exclusions, organization policies, audit logs, and IP indemnity Responsible AI principles — ethical considerations and Microsoft's framework (15–20% of the exam) Advanced features — Plan Mode, Agent Mode, Coding Agent, MCP, Copilot Spaces, and the REST API Why this course is different: Every lecture mirrors the scenario-based format of the actual exam. You get 34 focused lectures across 9 sections, 170 quiz questions for continuous self-assessment, and exam-day strategy covering time management and common traps. Who this course is for:Senior developers, tech leads, and architects preparing for the GitHub Copilot certification. You should have basic familiarity with an IDE and version control. No prior AI or machine learning experience is required.
62/100
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- What the provider tells you
- 38/45
- Who stands behind it
- 8/35
- How complete the listing is
- 16/20
Scores how much the provider publishes and who stands behind it — not how well it is taught.
What you'll learn
- Understanding how GitHub Copilot works
- Applying code completions and chat features across different IDEs
- Employing effective prompt engineering techniques
- Implementing code generation and refactoring
- Utilizing test generation strategies with Copilot
- Understanding privacy fundamentals related to AI use
- Applying responsible AI principles in practice
- Leveraging advanced features such as Plan Mode and REST API
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