AI Tools & Automation · PPL

GitHub Copilot for Developers Certification

A practical program that teaches developers to use GitHub Copilot for AI-assisted coding, debugging, testing, documentation, and software development.

  • 3 DaysDuration
  • PPLAccredited
  • 3 LanguagesArabic · English · Hindi
  • ₹6,499.00 Per delegate

This course is accredited by PPL

This is for all ppl accredited courses
2M+ Delegates trained worldwide
15,000+ Corporate clients
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4.8 ★ Average learner rating
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— The journey

Course Outline

What the programme covers, module by module.

Module 1: Introduction to GitHub Copilot

  • AI coding assistants
  • GitHub Copilot overview
  • Features
  • Benefits
  • Limitations
  • Responsible AI

Module 2: Getting Started with GitHub Copilot

  • Installation
  • IDE integration
  • Configuration
  • User settings
  • Subscription options
  • Development workflow

Module 3: Prompt Engineering for Coding

  • Code prompts
  • Context management
  • Prompt refinement
  • Task-specific prompting
  • Multi-step prompts
  • Best practices

Module 4: AI-Assisted Code Generation

  • Function generation
  • Boilerplate code
  • Code completion
  • Class generation
  • Template creation
  • Productivity techniques

Module 5: Debugging with Copilot

  • Error analysis
  • Bug fixing
  • Exception handling
  • Code troubleshooting
  • Performance issues
  • Debugging workflows

Module 6: Code Refactoring

  • Code optimization
  • Readability improvements
  • Performance enhancement
  • Clean code
  • Maintainability
  • Refactoring strategies

Module 7: Unit Testing with AI

  • Test generation
  • Unit tests
  • Test cases
  • Edge cases
  • Assertions
  • Test optimization

Module 8: Documentation Generation

  • Code documentation
  • Comments
  • README creation
  • API documentation
  • Technical documentation
  • Documentation standards

Module 9: API Development

  • REST APIs
  • Endpoint generation
  • Request validation
  • Response handling
  • API documentation
  • Integration support

Module 10: Database Development

  • SQL generation
  • CRUD operations
  • Query optimization
  • Database integration
  • Schema design
  • Data validation

Module 11: Code Reviews with AI

  • Code review assistance
  • Best practice recommendations
  • Security checks
  • Performance suggestions
  • Code quality
  • Review workflows

Module 12: Security & Secure Coding

  • Secure coding
  • Vulnerability detection
  • Input validation
  • Authentication concepts
  • Authorization concepts
  • Security best practices

Module 13: AI for DevOps

  • CI/CD support
  • Build scripts
  • Deployment automation
  • Infrastructure scripts
  • Configuration generation
  • Workflow optimization

Module 14: AI for Documentation & Communication

  • Technical writing
  • Change logs
  • Release notes
  • Team documentation
  • Knowledge sharing
  • Productivity enhancement

Module 15: Working with Multiple Programming Languages

  • Language-specific prompts
  • Cross-language development
  • Framework assistance
  • Code conversion
  • Multi-language projects
  • Best practices

Module 16: GitHub Copilot Chat

  • Conversational coding
  • Code explanations
  • Problem solving
  • Architecture discussions
  • Learning assistance
  • Interactive workflows

Module 17: AI Productivity Techniques

  • Daily coding workflows
  • Prompt libraries
  • Task automation
  • Time-saving strategies
  • Developer productivity
  • Workflow optimization

Module 18: Responsible AI for Developers

  • AI ethics
  • Code ownership
  • Licensing awareness
  • AI limitations
  • Human review
  • Compliance considerations

Module 19: Real-World Development Projects

  • Web applications
  • APIs
  • Automation scripts
  • Database applications
  • Software utilities
  • Practical exercises

Module 20: Emerging AI Development Trends

  • AI coding agents
  • Intelligent automation
  • Pair programming
  • AI-assisted software engineering
  • Future technologies
  • Industry trends

Module 21: Portfolio Development

  • GitHub portfolio
  • Code organization
  • Project documentation
  • Professional repositories
  • Showcase projects
  • Career readiness

Module 22: Professional AI Development Practices

  • Development standards
  • Collaboration
  • Code quality
  • Continuous learning
  • AI governance
  • Industry best practices 
— 01.2 · Is it right for you?

Who it's for & what's included

Pick a delivery method to see exactly who it suits and everything you receive.

Who it's for

Classroom

Best for learners who want face-to-face tuition and to network with peers in person.

What's included

Everything you get

  • Live instructor on-site
  • Printed workbook & materials
  • Group exercises & case studies
Who it's for

Online Instructor-Led

Best for learners who want a live instructor and a fixed schedule, without the travel.

What's included

Everything you get

  • Live instructor via video call
  • Digital workbook & resources
  • Session recordings
Who it's for

Self-Paced

Best for self-motivated learners who need maximum flexibility around work and life.

What's included

Everything you get

  • On-demand video lessons
  • Interactive quizzes
  • 24/7 access on any device
— What you will master

Course Objectives

01

Understand GitHub Copilot and its role in AI-assisted software development.

02

Generate code, tests, documentation, and APIs using AI-powered coding assistance.

03

Apply prompt engineering techniques to improve AI-generated coding results.

04

Debug, refactor, and optimize applications using GitHub Copilot effectively.

05

Improve software quality through AI-assisted testing, code reviews, and secure coding practices.

06

Integrate GitHub Copilot into modern software development and DevOps workflows.

07

Apply responsible AI practices while maintaining code quality, security, and compliance.

08

Improve developer productivity by automating repetitive coding and documentation tasks.

— Questions answered

Frequently Asked Questions

What is GitHub Copilot for Developers?
This course teaches developers how to use GitHub Copilot to accelerate coding, debugging, testing, documentation, and software development workflows.
Who should attend this course?
This course is suitable for software developers, backend developers, frontend developers, full-stack developers, DevOps engineers, and technical professionals.
Do I need programming experience?
Yes. This practitioner-level course is designed for developers who already have programming knowledge and want to improve productivity using AI.
What practical skills will I gain?
You will learn AI-assisted code generation, debugging, testing, documentation, API development, code reviews, DevOps automation, prompt engineering, and GitHub Copilot best practices.
How will this course benefit my career?
The course helps you write better code faster, automate repetitive development tasks, improve software quality, and develop AI-assisted programming skills that are increasingly valuable in modern software engineering.
— Trusted by learners

What our delegates say

★★★★★

"The structure, the practice exams, the instructor — all top tier. Passed first try."

AS
Aarti SharmaSenior Project Manager · TCS
★★★★★

"Best training I have attended. The content is exactly what modern projects need."

JD
James DonovanProgramme Director · Capgemini
★★★★★

"24/7 support actually means 24/7 — got help on my mock exam at 2am. Worth every dollar."

MO
Maya OkaforPMO Lead · Standard Bank

★ 4.8 / 5 from 12,000+ verified learner reviews on Trustpilot & Google.

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