Tool or Technology
TT0035

GitHub Copilot in Action

Build, Debug & Accelerate Development with AI

GitHub Copilot
Duration
16 Hours
Level
Intermediate
Delivery
Instructor-Led
Format
Capability Training

Programme Objectives

  • Develop functional proficiency in using GitHub Copilot across coding, codebase understanding, feature development, debugging, testing, and code review.
  • Apply effective prompt and context-engineering techniques to generate more relevant, maintainable, and project-aware code.
  • Use Plan Mode and Agent Mode to analyse requirements, plan changes, implement multi-file features, and iteratively resolve development issues.
  • Build reusable AI-assisted development practices using custom instructions, agent skills, repository context, and external tools through MCP.
  • Apply secure coding, code validation, human review, and software-quality practices when working with AI-generated code.

Technology covered

GitHub CopilotCopilot ChatCode SuggestionsAsk ModePlan ModeAgent ModeGitHub Copilot Coding AgentCopilot Code ReviewCustom InstructionsAgent SkillsModel Context Protocol (MCP)

Who should attend

  • Software Developers
  • Application Developers
  • Full-Stack Developers
  • Frontend Developers
  • Backend Developers
  • Software Engineers
  • QA & Test Automation Engineers
  • DevOps & Platform Engineers
  • Technical Leads
  • Solution Architects
  • Engineering Managers
  • Application Support & Maintenance Engineers

Prerequisites & Participant Readiness

  • Basic programming proficiency in at least one programming language
  • Familiarity with source-code files, functions, classes, APIs, and basic software-development concepts
  • Basic experience working with an IDE such as Visual Studio Code, Visual Studio, JetBrains IDEs, or another supported environment
  • Basic understanding of Git and GitHub is recommended
  • Familiarity with debugging and software testing concepts is beneficial
  • Access to certain capabilities may depend on the participant's GitHub Copilot plan and organisational policies
  • Completion of shorter GitHub Copilot programmes is not required

TOC Modules

Concepts
  • Understanding Generative AI and its role in modern software development
  • Understanding GitHub Copilot across IDE, GitHub, and developer workflows
  • Exploring code suggestions, Chat, Agents, and code-review capabilities
  • Understanding strengths, limitations, hallucinations, and developer accountability
  • Identifying appropriate versus inappropriate uses of AI-generated code
Practical activities
  • Configuring GitHub Copilot within a supported development environment
  • Exploring Copilot through common development activities
  • Comparing traditional and Copilot-assisted implementation approaches

Scenarios

Requirement to Production-Ready Feature

Business Requirement → Codebase Analysis → Plan Mode → Agent Mode → Multi-File Implementation → Testing → Refactoring → Copilot Code Review → Developer Approval

Participants use GitHub Copilot across the complete feature-development lifecycle to understand an existing repository, plan changes, implement a feature, test the solution, improve code quality, and prepare it for human-reviewed integration.

Production Defect to Verified Resolution

Bug Report → Repository Investigation → Logs / Error Analysis → Root-Cause Identification → Code Fix → Regression Tests → Copilot Review → Verified Resolution

Participants use GitHub Copilot to investigate a realistic software defect, identify the likely root cause, implement and validate a fix, and improve debugging and maintenance efficiency.

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