microsoft/Mastering-GitHub-Copilot-for-Paired-Programming
Mastering GitHub Copilot For Paired Programming
This project is a collection of educational resources and curricula designed for mastering AI pair programming and prompt engineering. It provides a structured training course and instructional materials for integrating AI assistants into the software development lifecycle.
The materials cover the use of large language models to modernize legacy code and translate applications between programming languages. It includes a specific guide for crafting natural language queries to generate code and automate development workflows.
The content addresses a broad range of capabilities, including AI-assisted refactoring, autonomous lifecycle management from planning to deployment, and AI-driven data exploration and query optimization. It also covers AI terminal integration and guided cloud deployment.
Features
- AI Pair Programming - Focuses on the core practice of collaborative software development where an AI agent assists in real-time coding.
- AI-Powered Code Generation - Teaches how to use generative models to suggest, complete, and refactor code in real time.
- Developer AI Assistance - Provides instructional materials on using context-aware AI tools integrated into coding environments.
- Prompt Engineering Guides - Offers comprehensive resources for developing and optimizing prompts for language models.
- AI Prompt Engineering - Provides specialized instructions and techniques for interacting with language models to generate complex code.
- AI Tooling Courses - Provides a multi-module educational program for mastering GitHub Copilot as a peer programming resource.
- AI-Assisted Programming Tutorials - Provides structured instructional guides on utilizing AI coding assistants and pair programming tools.
- Development Lifecycle Management - Covers the process of managing software engineering tasks from planning to implementation using AI assistants.
- Source Code Translations - Offers a guided workflow for rewriting existing applications from one programming language to another using AI.
- Large Language Model Tutorials - Provides practical guides and notebooks for using LLMs to modernize legacy code and translate languages.
- AI-Driven Refactoring - Provides instructions on using generative AI to restructure codebases and remove technical debt.
- AI-Driven Development Workflows - Explains the LLM-driven cycle of planning, execution, and verification for the software development lifecycle.
- Code Modernization Guides - Provides best practices for updating legacy software to modern standards using AI-assisted tools.
