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Microsoft Copilot Showcase

Empower Your Development Workflow with AI

Course Summary

In this course, students will delve into the practical applications of AI generation using Microsoft Copilot. Throughout the session, they will explore Copilot's AI capabilities for code generation, enhanced searches, plugin utilization, and more, equipping themselves with essential skills in harnessing AI. The session concludes with a brief discussion session, offering students the chance to strategize on leveraging Copilot effectively to drive value within their professional roles.

Learn practical applications of AI generation using Microsoft Copilot.

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

Familiarity with version control concepts, particularly using Git and GitHub

Proficiency in using a code editor, ideally Visual Studio Code

IT professionals
Skill level
Lecture | Hands-on Activities
4 hr. Targeted Topic
Related technologies
Java | Python | C# | Git | 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 Microsoft Copilot Live Demonstrations
    • What is Microsoft 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 Microsoft 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 Live Demonstrations
    • 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 Live Demonstrations
    • 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
  • Where to Go from Here
    • Research Copilot’s Plugins: Overview of Copilot plugins and their role in extending Copilot's functionality with additional features and integrations
    • Customizing Copilot: How to customize Copilot's behavior and suggestions to better suit individual coding preferences and project requirements

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By filling out this form and clicking submit, you acknowledge our privacy policy.