Tool or Technology
TT0036

Mastering GitHub Copilot

Advanced Agentic Development, Automation & AI Engineering Workflows

GitHub Copilot
Duration
32 Hours
Level
Advanced
Delivery
Instructor-Led
Format
Capability Development

Programme Objectives

  • Develop advanced expertise in using GitHub Copilot across planning, coding, refactoring, debugging, testing, code review, and software-delivery workflows.
  • Architect agentic development workflows using Copilot agents, custom instructions, reusable Skills, custom agents, MCP-connected tools, and repository context.
  • Delegate complex development work across IDE, terminal, GitHub, and cloud-based agent environments while maintaining effective developer oversight.
  • Automate repeatable engineering activities using Hooks, GitHub Actions, agentic workflows, code-review automation, and repository-level customisation.
  • Apply secure AI-assisted development practices covering code quality, permissions, secrets, governance, review controls, and responsible use.

Technology covered

GitHub CopilotCopilot ChatAgent ModeCopilot Cloud AgentGitHub Copilot CLICopilot Code ReviewGitHub Copilot AppCustom InstructionsPrompt FilesCustom AgentsAgent SkillsPluginsModel Context Protocol (MCP)HooksCopilot MemoryGitHub Actions & Agentic Workflows

Who should attend

  • Software Developers & Application Engineers
  • Full-Stack Developers
  • Frontend & Backend Developers
  • Technical Leads & Engineering Leads
  • Software Architects & Solution Architects
  • DevOps & Platform Engineers
  • QA & Test Automation Engineers
  • Cloud Engineers
  • Site Reliability Engineers
  • Engineering Managers
  • Application Modernisation Teams
  • Developer Productivity & Platform Teams
  • Security-Focused Development Teams
  • GitHub Administrators & Enterprise Engineering Teams
  • AI-Assisted Development & Innovation Teams

Prerequisites & Participant Readiness

  • Working knowledge of at least one programming language
  • Familiarity with Git, GitHub repositories, branches, commits, and pull requests
  • Basic experience with an IDE such as Visual Studio Code, Visual Studio, or JetBrains
  • Familiarity with software development, debugging, and testing concepts
  • Command-line familiarity is recommended for Copilot CLI activities
  • Basic understanding of APIs and development tooling is beneficial for MCP and advanced integrations
  • Access to some advanced capabilities may depend on Copilot plan, repository policies, organisation settings, IDE, and feature availability
  • Completion of shorter GitHub Copilot programmes is not required

TOC Modules

Concepts
  • Understanding GitHub Copilot across IDE, terminal, GitHub, and agentic development environments
  • Understanding completions, Chat, Agents, Code Review, CLI, and cloud-based development
  • Understanding context, repository awareness, tool use, and model capabilities
  • Differentiating developer-assistive and autonomous agentic workflows
  • Understanding AI-generated code limitations and developer accountability
Practical activities
  • Exploring GitHub Copilot across realistic development activities
  • Comparing manual, AI-assisted, and agent-driven approaches to engineering tasks
  • Identifying high-value Copilot opportunities across the software development lifecycle

Scenarios

Requirement-to-Production Development Workflow

Product Requirement → GitHub Issue → Copilot Planning → Cloud / IDE Agent → Multi-File Development → Automated Tests → Copilot Code Review → Human Review → Pull Request

Participants design an end-to-end AI-assisted software-delivery workflow that moves from requirement analysis through implementation, testing, review, and pull-request readiness while maintaining developer oversight and engineering standards.

Enterprise Engineering Automation

Recurring Repository Task → Agentic Workflow → Custom Agent / Skill → MCP Context → Copilot Execution → Hooks & Validation → Code Review → Human Approval

Participants automate a repeatable engineering activity such as dependency maintenance, documentation updates, test improvement, or repository quality checks using agentic GitHub capabilities with controlled validation and governance.

Related programmes

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