GitHub Copilot (GH-300)

Bring AI assistance into your development workflow

Copilot supports more than code completion. This one-day course helps developers and DevOps professionals use its capabilities across the software development lifecycle, while retaining responsibility for correctness, quality and security. You will explore practical ways to make Copilot useful within the IDE, command line and GitHub rather than relying on generated suggestions without review.

Work effectively with Copilot

Examine inline suggestions, chat, Copilot CLI and agent mode, including when to use each experience. Discover how to shape useful prompts with relevant repository context, examples and clear acceptance criteria. Explore reusable instructions and prompt files, and consider how agent sessions, sub-agents and MCP-connected tools can support more involved development activities.

Improve code, tests and collaboration

Learn where Copilot can assist with drafting, understanding, refactoring and documenting code. Consider the value of generated unit and integration tests, edge-case identification and performance or security suggestions. Explore pull request summaries, Copilot code review and the need to review changes.

Understand data handling and safeguards

Review how prompts and context are processed, where Copilot's limitations arise and how different plans and organisational settings affect use. Understand content exclusions, public-code matching controls, privacy choices and auditability. Discuss responsible AI principles and the importance of validating output before it reaches a shared repository.

Prepare for GitHub certification

The course aligns with the GH-300 study guide effective 7 August 2026. It provides structured coverage of core features, prompt engineering, architecture, developer productivity and governance. Prior coding and GitHub experience will help you apply the material, and further personal practice may be useful before the assessment.