Build reliable, maintainable software by combining Test-Driven Development with AI-assisted engineering using GitHub Copilot.

This hands-on training helps software teams use GitHub Copilot as a collaborative development partner while maintaining strong engineering standards. Participants learn practical TDD, clean code, refactoring, legacy modernization, and sustainable AI-assisted development workflows.

  • Why get trained: Learn TDD, AI-assisted coding, effective testing, refactoring, clean code, and safe techniques for working with legacy codebases.
  • Why it matters: Increase development productivity while maintaining software quality, testability, maintainability, and engineering accountability.
  • Who should attend: Software Engineers, Full Stack Developers, Backend Developers, Frontend Developers, Technical Leads, Engineering Managers, QA Automation Engineers, Developers new to TDD, and Teams adopting AI-assisted development.

Participants gain practical experience through real-world simulations, hands-on workshops, and practitioner guidance to build sustainable AI-assisted engineering workflows. HRD Corp Claimable.

Overview

As AI coding assistants become increasingly common in software development, engineering teams face a new challenge: how to increase productivity without compromising software quality, maintainability, and engineering standards.

This training helps participants combine Test-Driven Development (TDD) with GitHub Copilot to create sustainable AI-assisted engineering workflows. Rather than relying solely on AI-generated code, participants learn how to use AI as a collaborative development partner while maintaining accountability for software design and quality.

Throughout the training, learners explore practical techniques for writing effective tests, improving code quality through refactoring, reducing technical debt, and modernizing legacy applications. They also discover how AI-assisted workflows can support clean code practices and continuous improvement.

By combining proven engineering disciplines with AI-powered development tools, teams can build software faster while maintaining confidence, quality, and long-term maintainability.

Skills Covered

  • Understand TDD principles and engineering benefits
  • Understand the role of AI coding assistants in software development
  • Apply AI-assisted engineering responsibly
  • Use the Red → Green → Refactor workflow
  • Write effective unit tests
  • Design maintainable test suites
  • Improve code quality through refactoring
  • Use Copilot for test, code and refactor
  • Improve productivity without sacrificing engineering quality
  • Apply clean code principles
  • Reduce complexity and duplication
  • Improve readability and testability
  • Refactor safely using AI-assisted workflows
  • Apply TDD to existing codebases
  • Improve test coverage incrementally
  • Break dependencies safely
  • Introduce seams and extensibility points
  • Understand CI/CD integration with TDD
  • Improve quality gates and automation workflows
  • Build sustainable AI-assisted engineering systems

Prerequisites

None

Target Audience

  • Software Engineers
  • Full Stack Developers
  • Backend Developers
  • Frontend Developers
  • Technical Leads
  • Engineering Managers
  • QA Automation Engineers
  • Developers new to TDD
  • Teams adopting AI-assisted development

Course Curriculum

Module 1: AI-First Engineering & Modern Development Workflows

This module introduces the shift toward AI-assisted software engineering and explains how GitHub Copilot changes modern development workflows. Participants learn how AI coding assistants support productivity while maintaining engineering accountability and quality.

Module 2: Unit Testing Fundamentals

This module introduces core testing concepts and explains how unit testing improves software quality, maintainability, and confidence during development.

Module 3: Introduction to Test-Driven Development (TDD)

Participants learn the fundamentals of Test-Driven Development and how AI-assisted workflows can accelerate and improve TDD practices.

Module 4: Driving Development with AI-Assisted TDD

This module focuses on practical implementation workflows where GitHub Copilot supports development, testing, and iterative refinement.

Module 5: Emergent Design & Refactoring with Copilot

This module focuses on improving software design incrementally using refactoring techniques and AI-assisted engineering workflows.

Module 6: Working with Legacy Code

Participants learn practical strategies for introducing TDD into existing systems and improving legacy code safely using AI-assisted techniques.

Module 7: Continuous Integration & Engineering Quality

This module explains how TDD integrates into modern engineering workflows and quality systems. Participants learn how to maintain quality through automation and engineering discipline.

Module 8: Capstone: AI-Assisted Engineering Workflow

Participants apply everything learned during the training to implement a complete AI-assisted engineering workflow using TDD and GitHub Copilot.

 

Dates & Locations

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Exam & Certification

Complete the AI-Assisted Test-Driven Development with GitHub Copilot Training and receive your AI-Assisted Test-Driven Development with GitHub Copilot Training Certificate of Completion after successfully completing the program. This validates your skills in applying Test-Driven Development with GitHub Copilot, writing effective tests, refactoring safely, improving code quality, reducing technical debt, and building sustainable AI-assisted engineering workflows.

Training & Certification Guide

Yes. Participants who complete the training will receive a Certificate of Completion recognizing their participation and understanding of AI-assisted test-driven development practices.

Why train with Trainocate

This hands-on training teaches software professionals how to combine Test-Driven Development (TDD) with GitHub Copilot to build high-quality software faster. Participants learn testing, refactoring, AI-assisted coding, and modern engineering practices.

Yes. The workshop introduces TDD fundamentals and gradually progresses to advanced AI-assisted TDD workflows, making it suitable for both beginners and experienced developers.

GitHub Copilot can help generate tests, suggest implementation code, support refactoring activities, and accelerate development cycles while developers maintain control over quality and design decisions.

Yes. Participants learn practical techniques for introducing tests into existing systems, reducing technical debt, improving test coverage, and modernizing legacy applications safely.

Yes. The workshop includes coding labs, pair programming exercises, refactoring activities, live demonstrations, and real-world software engineering scenarios.

The training focuses on writing effective tests, applying clean code principles, reducing complexity, improving maintainability, and using AI responsibly to support engineering excellence.

Yes. Organizations increasingly seek developers who can effectively combine AI-assisted development tools with strong engineering practices. These skills can help professionals remain competitive in modern software development environments.

You will gain practical experience in Test-Driven Development, GitHub Copilot workflows, unit testing, refactoring, legacy code modernization, AI-assisted engineering, and continuous quality improvement practices.

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