This course explores the practical applications of GitHub CoPilot for Quality Engineering.  CoPilot can integrate with the JetBrains Integrated Development Environments and Microsoft Visual Studio Code IDEs. But, this course will use Visual Studio Code as the IDE interface for CoPilot.  

The potential scope of technical material demonstrated practically with CoPilot would be massive.  To focus the course to a more manageable scope, this course will use CoPilot on: Java Spring Boot with Mockito & JUnit and Java Maven with Cucumber & Selenium.  If you are unfamiliar with these languages or frameworks, you can still work through this course. The focus is on the interface usage and prompt engineering to empower productivity for quality engineering. You'll be able to apply the same techniques you learn here with the languages & frameworks you do know.


Java is a powerful programming language that forms the backbone of countless applications, from mobile apps to large-scale enterprise systems. Its object-oriented nature and robust security features make it a preferred choice for developers around the globe.

Then we have Spring Boot, a powerful extension of the Java framework, which has revolutionized the way developers create web applications and microservices. Its convention-over-configuration approach, coupled with its ability to effortlessly integrate with various systems, makes it a go-to choice for building scalable and maintainable applications.

Enter GitHub Copilot, an AI-powered code completion tool that revolutionizes the way developers write code. With Copilot, you can streamline your coding process, reduce errors, and explore new programming possibilities. It acts as your virtual coding assistant, offering real-time suggestions and insights that can help you write more efficient and effective Java code.


Github Copilot is a powerful code generation tool that can be used within a variety of development environments. In this course, we'll be looking at using Copilot to help us in the development of React applications. 

Though it can be useful within React to quickly setup an application's functionality—like creating functions or generating forms—it can also be used to help with styling and laying out elements. But beyond the obvious, it can also help us in other key areas like testing, documentation, and debugging.


In this path, we focus on Data Engineer skills for the ETL process. You will review concepts covering SQL for data base management skills, NumPy and Pandas for small scale data manipulation, Data Warehousing and PySpark for large scale data manipulation, tools for visualization, and cloud integration. With an understanding of these fundamental concepts in these topics, we will dive into how you can apply GitHub Copilot to expedite the entire ETL process from a coding standpoint.