GitHub Copilot for Developers: Code Faster With AI Agents

本课程旨在帮助开发者超越GitHub Copilot的基础自动补全功能，全面掌握其作为AI工程助手的强大能力。课程分为三大阶段：首先深入解析AI的工作机理，包括提示词、令牌、模型选择及上下文窗口等核心概念；其次聚焦实战，教授如何利用Copilot的Agent、Ask、Plan和Edit等模式高效进行代码生成、调试、重构与测试；最后进入高级代理开发，指导学员创建自定义指令文件、构建专属AI代理，并设计本地、后台及云端代理协同的工作流。通过本课程，开发者将学会将AI深度集成到开发生命周期中，从而成倍提升编码效率与软件质量。

制作人：Shubham Sarda
MP4格式 | 视频：h264编码，1920×1080分辨率 | 语言：英语 | 时长：34节课（4小时19分钟） | 文件大小：2.56 GB

GitHub Copilot for Developers: Code Faster With AI Agents
Master AI agent-powered coding workflows with GitHub Copilot and learn how modern developers code faster and smarter

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.

Requirements
● Basic knowledge of Programming
● Basic knowledge of Git & Github

Description
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 Learn

You will learn how to

• Generate production-ready code using structured prompts

• Fix bugs, refactor legacy code, and improve readability

• Automatically generate meaningful unit tests

• Improve performance and detect potential security issues

• Use Agent, Ask, Plan, and Edit modes effectively

• Create powerful instruction files to control AI behaviour

• Build and manage custom AI agents

• Design workflows using Local, Background, and Cloud agents

• Understand MCP (Model Context Protocol) and modern AI tooling

• Integrate AI deeply into your development lifecycle

The course has been divided into 3 Phases,

Phase 1: Foundations / How AI Coding Actually Works
Before 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 windows

• Tokens and how they affect output quality

• Models and how to choose the right one

• LLM vs SLM differences

• How tools like Copilot, Cursor, Claude Code, Codex, and others differ

This phase gives you the mental model required to control AI instead of randomly guessing prompts.

Phase 2: Practical Copilot Usage
Here we move into real development workflows.

You will learn

• Proper Copilot setup and configuration

• Inline suggestions vs chat-based workflows

• Using the chat window effectively

• Understanding and using Agent, Ask, Plan, and Edit modes

• Managing sessions and checkpoints

• Using the built-in browser

• Bring Your Own Key configuration

This phase focuses on practical usage so you can immediately apply Copilot in daily development.

Phase 3: Advanced Agentic Development
This 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 workflows

• Custom agents tailored to your project needs

• Agent skills for specialised tasks

• Local agents vs background agents vs cloud agents

• Git integration and smart actions

• MCP (Model Context Protocol) for advanced integrations

• AI code security best practices

By 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.

Who this course is for
■ Developers who already know how to code and want to work faster using AI
■ Computer science students who want to learn AI-assisted development from the right foundation
■ Working professionals who want to integrate GitHub Copilot into real-world workflows
■ Engineers curious about AI Agents and modern AI-powered software development
■ Anyone who can write code and wants to 2x–5x their productivity using structured AI workflows