GitHub Copilot for Software Developers (Video Course)

Description

3 Hours of Video Content

Accelerate development, write efficient code, and improve productivity.

Overview:

GitHub Copilot is an AI-powered coding assistant that helps software developers write code faster and more efficiently by providing intelligent suggestions and automating repetitive tasks. As businesses increasingly rely on software, the demand for faster development and higher-quality code has never been greater. This technology is a game-changer because it reduces development time, minimizes errors, and allows developers to focus on creative problem-solving rather than tedious coding tasks.

This course provides a hands-on, practical approach to mastering Copilot, ensuring developers can integrate it effectively into their workflow. We will cover installation and configuration, optimize code suggestions, automate repetitive tasks, enhance debugging, and write tests and documentation with AI assistance. By the end of the course, participants will understand Copilots capabilities, limitations, and best practices to maximize productivity while maintaining high-quality code.

Skill Level:

• Intermediate

Learn How To:

• Install and configure GitHub Copilot in various IDEs.
• Generate, refactor, and optimize code using AI-powered suggestions.
• Automate repetitive coding tasks to enhance workflow efficiency.
• Write clear documentation and unit tests with AI assistance.

In addition, you'll learn more advanced features such as how to:

• Customize Copilot for more relevant and precise code suggestions.
• Use AI to detect, debug, and resolve performance issues.
• Implement best practices to avoid over-reliance on AI-generated code.
• Explore Copilot Labs and future advancements in AI-driven development.

Course requirements:

• Basic Programming Knowledge
• Experience with an Integrated Development Environment (IDE)
• Fundamental Software Development Concepts

Who Should Take This Course:

• Software Developers
• Software Engineers
• Full-Stack Developers
• Frontend and Backend Developers
• DevOps Engineers

About Pearson Video Training:   

Pearson publishes expert-led video tutorials covering a wide selection of technology topics designed to teach you the skills you need to succeed. These professional and personal technology videos feature world-leading author instructors published by your trusted technology brands: Addison-Wesley, Cisco Press, Pearson IT Certification, Prentice Hall, Sams, and Que Topics include IT Certification, Network Security, Cisco Technology, Programming, Web Development, Mobile Development, and more.  Learn more about Pearson Video training at  http://www.informit.com/video.

Video Lessons are available for download for offline viewing within the streaming format. Look for the green arrow in each lesson.

Sample Content

Table of Contents

Introduction

Lesson 1: Introducing GitHub Copilot

1.1 Learn what GitHub Copilot is and how it works

1.2 Learn about supported languages and environments

Lesson 2: Learn About Code Generation and Completion

2.1 Generate functions from comments

2.2 Create boilerplate code and project templates

2.3 Refactor code with Copilot suggestions

2.4 Optimize performance with AI assistance

Lesson 3: Debug with GitHub Copilot

3.1 Use Copilot to detect and fix errors

3.2 Enhance debugging with AI-powered suggestions

3.3 Integrate Copilot with debugging tools

Lesson 4: Write Documentation with Copilot

4.1 Generate meaningful code comments and docstrings

4.2 Create well-structured README files

4.3 Automate API documentation with markdown

4.4 Improve documentation consistency and readability

Lesson 5: Create Tests with Copilot

5.1 Generate unit tests from function definitions

5.2 Use Copilot with popular testing frameworks

5.3 Expand test coverage and edge cases

5.4 Automate repetitive test writing tasks

Lesson 6: Learn Advanced Tips and Best Practices

6.1 Maximize Copilots potential and limitations

6.2 Learn about ethical AI coding and avoiding over-reliance

6.3 Explore Copilot labs and future enhancements

Summary

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