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GitHub Copilot

Course Summary

This course explores the use of generative AI through GitHub Copilot. Participants will immerse themselves in the practical applications of AI generation and will learn about Copilot's AI capabilities for code generation, enhanced searches, plugin utilization, and more. In-class hands-on practices allow learners to gain experience harnessing the power of Gen AI within Copilot's innovative platform.

Purpose
Learn about Copilot's AI capabilities for code generation, enhanced searches, plugin utilization, and more.
Prerequisites

Basic understanding of programming concepts and syntax in at least one programming language (e.g., Python, JavaScript, Java)

Familiarity with version control concepts, particularly using Git and GitHub

Proficiency in using a code editor, ideally Visual Studio Code

Role
IT Professionals
Skill level
Intermediate
Style
Lecture | Hands-on Activities
Duration
1 day
Related technologies
Generative AI | Python | JavaScript | Java | Visual Studio

 

Learning objectives
  • Understand the fundamentals of generative AI and its practical applications
  • Improve coding efficiency by leveraging Copilot's AI capabilities for code completion, documentation, and error handling
  • Collaborate more efficiently with teammates by incorporating Copilot into version control workflows

What you'll learn:

In this course, you'll learn:
  • Introduction to Generative AI
    • Definition and significance of generative AI
    • Overview of applications across industries
    • Basics of natural language generation
  • Introduction to GitHub Copilot
    • What is GitHub Copilot? Explanation of its features and capabilities, including code generation, completion, and suggestions
    • Advantages and Examples: How Copilot can streamline coding workflows, enhance productivity, and improve code quality
    • Setting up GitHub Copilot: Installing Copilot in your Integrated Development Environment (IDE)
    • Navigating the interface: Overview of Copilot's user interface elements, including the suggestion panel, input/output sections, and context-aware suggestions
  • Developing with GitHub Copilot
    • Code simplification and optimization: How Copilot can assist in simplifying complex code snippets, optimizing algorithms, and improving code readability
    • Error handling: Using Copilot to identify and handle errors in code, including suggestions for debugging and error resolution
    • Inline documentation: Utilizing Copilot to generate inline comments, documentation, and code explanations
    • Test generation: Exploring Copilot's capabilities for generating test cases and automating testing processes
  • Maximizing Efficiency
    • Settings and customizations: Overview of Copilot's settings and customization options, including language preferences, code style preferences, and plugin integrations
    • Shortcuts and commands: Learning useful keyboard shortcuts and commands for efficient navigation and interaction with Copilot
    • Integrating with Git and GitHub: How to seamlessly integrate Copilot into your Git and GitHub workflows for version control and collaboration
    • Exploring limitations and considerations: Discussion on the limitations and ethical considerations of using AI-driven tools like Copilot in software development
  • Advanced Usage
    • Plugins: Overview of Copilot plugins and their role in extending Copilot's functionality with additional features and integrations
    • Exploring advanced features: Delving deeper into Copilot's advanced features, such as natural language understanding, refactoring assistance, and optimization techniques
    • Customization options: How to customize Copilot's behavior and suggestions to better suit individual coding preferences and project requirements

GitHub Copilot

real world content

Real-World Content

Project-focused demos and labs using your tool stack and environment, not some canned "training room" lab.
expert practitioners

Expert Practitioners

Industry experts that bring their battle scars into the classroom.
experiential learning

Experiential Learning

More coding than lecture, coupled with architectural and design discussions.
fully customized

Tailored Outlines

Once-size-fits-all doesn't apply to training teams. That's where we come in!

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