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URL: https://www.coursera.org/learn/github-ai-augmented-testing-and-refactoring

⇱ GitHub: AI-Augmented Testing and Refactoring | Coursera

GitHub: AI-Augmented Testing and Refactoring

GitHub: AI-Augmented Testing and Refactoring

This course is part of Mastering GitHub Specialization

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Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

3 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

3 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Apply AI-assisted test-driven development to generate tests, mock dependencies, and evaluate test coverage using GitHub Copilot and PyTest

  • Analyze cross-file dependencies and execute system-wide code cleanup by leveraging @workspace references and style enforcement with GitHub Copilot

  • Create infrastructure-as-code configurations including Ansible playbooks, Dockerfiles, and Terraform modules using AI-assisted generation workflows

Details to know

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Recently updated!

April 2026

Assessments

4 assignments

Taught in English

Build your subject-matter expertise

This course is part of the Mastering GitHub Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 3 modules in this course

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.

Covers AI-assisted TDD fundamentals, generating complex test suites, mocking dependencies, hands-on TDD challenges, and evaluating test coverage with GitHub Copilot.

What's included

8 videos2 readings1 assignment

8 videos•Total 33 minutes
  • Course Introduction•1 minute
  • Introduction to AI-Assisted TDD•4 minutes
  • Generating Complex Test Suites•7 minutes
  • Mocking Dependencies with Copilot•4 minutes
  • Mocking Dependencies with Copilot•4 minutes
  • Challenge: TDD for a New Feature•2 minutes
  • Solving a Feature with TDD•5 minutes
  • Evaluating Test Coverage•5 minutes
2 readings•Total 2 minutes
  • Key Terms: AI-Assisted Test-Driven Development•1 minute
  • Reflection: AI-Assisted Test-Driven Development•1 minute
1 assignment•Total 5 minutes
  • AI-Assisted Test-Driven Development•5 minutes

Covers strategic workspace usage, cross-file dependency analysis, system-wide code cleanup, style enforcement, custom guidelines, infrastructure-as-code generation with Dockerfiles and Terraform, and course conclusion.

What's included

9 videos4 readings2 assignments

9 videos•Total 40 minutes
  • Generating IaC Configurations•4 minutes
  • Creating Dockerfiles with AI•4 minutes
  • Terraform Configuration Generation•4 minutes
  • Course Conclusion•2 minutes
  • Strategic Use of Workspace•5 minutes
  • Analyzing Cross-File Dependencies•4 minutes
  • Challenge: System-Wide Code Cleanup•4 minutes
  • Enforcing Styles and Constraints•8 minutes
  • Generating Guidelines for Specific Tasks•4 minutes
4 readings•Total 40 minutes
  • Key Terms: Infrastructure as Code Generation•10 minutes
  • Reflection: Infrastructure as Code Generation•10 minutes
  • Key Terms: System-Wide Refactoring and Code Quality•10 minutes
  • Reflection: System-Wide Refactoring and Code Quality•10 minutes
2 assignments•Total 35 minutes
  • System-wide refactoring•30 minutes
  • System-Wide Refactoring and Infrastructure as Code•5 minutes

Apply AI-assisted testing, system-wide refactoring, and infrastructure-as-code generation techniques in an end-to-end development scenario that synthesizes all course concepts.

What's included

1 reading1 assignment

1 reading•Total 10 minutes
  • Next steps•10 minutes
1 assignment•Total 30 minutes
  • AI-Augmented testing and Refactoring•30 minutes

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Instructor

Pragmatic AI Labs
35 Courses•2,961 learners

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Frequently asked questions

No. The course teaches Copilot techniques from the ground up, starting with test generation and building to complex workspace-level operations. Basic programming experience in Python or Rust is sufficient

The course uses Python with pytest for testing demonstrations and Rust for infrastructure-as-code and refactoring examples. You will work with real projects in both languages throughout the hands-on exercises.

Yes. The infrastructure-as-code module covers generating Ansible playbooks, Dockerfiles with distroless multi-stage builds, and Terraform configurations for cloud deployment — all using GitHub Copilot to accelerate the process.

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Financial aid available,