GitHub: AI-Augmented Testing and Refactoring
Key Takeaways
This video teaches how to accelerate software development workflow by combining GitHub Copilot with test-driven development, system-wide refactoring, and infrastructure-as-code generation
Original Description
Learn to accelerate your software development workflow by combining GitHub Copilot with test-driven development, system-wide refactoring, and infrastructure-as-code generation. This course teaches you to use AI assistance at every stage of code quality — from writing your first test to deploying containerized applications.
You will start with AI-assisted test-driven development, using GitHub Copilot to generate test cases, mock dependencies, and evaluate test coverage with pytest. You will then move to system-wide refactoring, leveraging @workspace references to analyze cross-file dependencies, enforce coding standards, and execute coordinated code cleanup across large codebases.
The course concludes with infrastructure-as-code generation, where you use Copilot to produce Ansible playbooks, Dockerfiles with distroless multi-stage builds, and Terraform configurations for cloud deployment. Each lesson includes hands-on challenges and solution walkthroughs using real Rust and Python projects.
By the end of this course, you will have a practical toolkit for integrating AI assistance into testing, refactoring, and infrastructure workflows — skills that directly reduce development cycle time while improving code quality.
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Tutor Explanation
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