About This Course
GitHub Copilot is no longer just an AI autocomplete tool. It is an AI-powered engineering assistant capable of generating features, refactoring systems, writing tests, reviewing security issues, and orchestrating complex workflows using agents.Most developers use only 10–20% of its capabilities.This course is designed to help you use GitHub Copilot properly, from understanding how it works to building structured AI workflows using instruction files, custom agents, and agent skills.This is not a theory-heavy AI course. It is a practical, developer-first mastery program focused on real coding workflows.What You Will LearnYou will learn how to:Generate production-ready code using structured promptsFix bugs, refactor legacy code, and improve readabilityAutomatically generate meaningful unit testsImprove performance and detect potential security issuesUse Agent, Ask, Plan, and Edit modes effectivelyCreate powerful instruction files to control AI behaviourBuild and manage custom AI agentsDesign workflows using Local, Background, and Cloud agentsUnderstand MCP (Model Context Protocol) and modern AI toolingIntegrate AI deeply into your development lifecycleThe course has been divided into 3 Phases,Phase 1: Foundations / How AI Coding Actually WorksBefore using AI effectively, you must understand how it thinks.In this phase, you will learn:What prompts are really (User vs System prompts)Context and context windowsTokens and how they affect output qualityModels and how to choose the right oneLLM vs SLM differencesHow tools like Copilot, Cursor, Claude Code, Codex, and others differThis phase gives you the mental model required to control AI instead of randomly guessing prompts.Phase 2: Practical Copilot UsageHere we move into real development workflows.You will learn:Proper Copilot setup and configurationInline suggestions vs chat-based workflowsUsing the chat window effectivelyUnderstanding and using Agent, Ask, Plan, and Edit modesManaging sessions and checkpointsUsing the built-in browserBring Your Own Key configurationThis phase focuses on practical usage so you can immediately apply Copilot in daily development.Phase 3: Advanced Agentic DevelopmentThis is where the course goes beyond basic Copilot tutorials.You will learn how to structure AI behaviour using:Instruction files (copilot-instructions and custom instructions)Prompt files for reusable AI workflowsCustom agents tailored to your project needsAgent skills for specialised tasksLocal agents vs background agents vs cloud agentsGit integration and smart actionsMCP (Model Context Protocol) for advanced integrationsAI code security best practicesBy the end of this phase, you will understand how to design a complete AI-powered engineering workflow rather than just asking Copilot random questions.If you can write code, this course will show you how to build faster, refactor smarter, and ship confidently using AI. The goal of this course is simple: To help you move from “using Copilot” to engineering with AI.
What you'll learn:
- Understand how GitHub Copilot works, including prompts, tokens, models, and context windows.
- Apply practical prompt engineering techniques to get accurate, production-ready code.
- Use Copilot for real-world tasks like code generation, bug fixing, refactoring, and documentation.
- Generate meaningful unit tests and improve performance using AI-powered suggestions.
- Identify potential security vulnerabilities and improve secure coding practices with AI.
- Master Copilot modes: Agent, Ask, Plan, and Edit, and know when to use each.
- Create and structure powerful Instruction Files to control AI behavior across projects.
- Build and manage Custom AI Agents with reusable prompt architecture and agent skills.
- Design workflows using Local, Background, and Cloud Agents for scalable AI-assisted development.
- Implement a complete AI-powered development workflow to code faster and ship high-quality software confidently.