Introduction to GitHub Copilot: Its features and benefits, supported IDES, languages, and configurations.
Prompt Engineering for Coding: Using Copilot for Code Suggestions and Completions and effectively writing code.
Cross-Language & Framework Support: Working with Copilot Across Programming Languages
Writing Tests and Debugging: Enhancing Debugging and Troubleshooting with Copilot
Real-World Code Generation: Customising Copilot for Specific Development Needs
Security and Responsible AI Use: Ethical Considerations and Limitations in AI-Assisted Coding
DevOps & Automation Scripting: Writing Dockerfiles, Kubernetes YAMLS, and shell scripts.
Productivity & Workflow Optimisation: to speed up repetitive tasks and boost productivity without over-relying on AI.

Should have a basic understanding of GitHub fundamentals.
Foundational knowledge of programming languages like Python, JavaScript, etc.
Knowledge of functions, loops, conditionals and basics of OOP concepts
Know how to install extensions and use the integrated terminal
Candidates must be familiar with GitHub repositories, version control, and workflows.
Understand GitHub workflow, like clone, push, pull, etc.
Have experience using GitHub Copilot and similar AI tools.
Efficiency to write prompts and refine suggestions.
Know how to debug and refactor AI-generated code.
Should understand and have experience using IDES.

Software Developers / Software Engineers use Copilot to speed up coding, testing, and debugging.
AI-Augmented Developer vital Github Copilot in daily workflow, along with AI assistance.
DevOps Engineer used Copilot to write YAML files, Dockerfiles, and shell scripts and automate infrastructure workflow.
QA Automation Engineer uses it to automate test cases, assertions, and streamline regression.
Web Developers use it to speed web development tasks by 30-50%.
Cloud Developer write infrastructure-as-code (Iac) for AWS, Azure, or GCP with Copilot
Integration Engineers generate REST API Endpoints, input validation, and documentation with it.
A low-code/AI Workflow Developer can combine GitHub Copilot with platforms to build smart automation.
Data Engineer / Data Analyst writes Python/Pandas scripts, great for automating repetitive analytics code blocks.
Open Source Contributor uses Copilot to prototype features, write tutorials, etc., to accelerate documentation and demos.

The certification improves coding efficiency with GitHub Copilot.
Increases the opportunity to integrate Copilot into daily workflows.
Improved problem-solving and debugging skills for developers.
Understanding the ethical practices of AI-assisted development.
Utilisation of GitHub Copilot across various environments is responsible for security.
Gain knowledge on the advanced functionalities of GitHub Copilot.
Understanding distinctions between GitHub Copilot Individuals, Business, and Enterprise.

Candidates, after the completion of this course, can explore advanced topics, like:

Candidates who want AI for developer productivity can choose

For those who are into DevOps and Automation

Candidates into Cloud Development can take

For testing and security code automations