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GitHub Copilot in Action: AI-driven Coding

Integrating AI to Accelerate Your Software Development and Improving Your Development Workflow

Duration

5 Days (4 hours per day)

Level

Basic Level

Design and Tailor this course

As per your team needs

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The course is designed to provide participants with a deep understanding of how GitHub Copilot can revolutionize their development workflows through AI-assisted coding. By the end of the course, learners will be proficient in installing, configuring, and optimizing GitHub Copilot within various programming environments, enabling them to seamlessly integrate it into their daily development tasks. Participants will explore advanced features of Copilot, such as language-specific customization and project-level optimization, to enhance coding efficiency and precision.

The course also covers best practices for utilizing Copilot, ensuring that users can balance productivity gains with maintaining code security and quality. Through hands-on labs and real-world case studies, learners will gain practical experience in applying Copilot across different scenarios, from automating repetitive coding tasks to debugging and testing complex codebases. Additionally, the course delves into the evolving role of AI in software development, equipping participants with the knowledge to leverage emerging AI-driven tools and technologies, while preparing them for future advancements in the field.

Key Takeaways:

  • Master the use of GitHub Copilot to generate, refactor, and improve code quickly and accurately
  • Enhance your ability to manage large codebases with AI-assisted coding tools
  • Customize and fine-tune Copilot to match your specific workflow needs and preferences
  • Gain hands-on experience through practical labs that showcase how Copilot integrates with various programming tasks
  • Understand the future of AI in software development and how it can reshape coding practices
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  • Software Developers and Engineers seeking AI tools to accelerate coding efficiency
  • Data Scientists aiming to automate repetitive coding tasks
  • DevOps Engineers interested in AI-powered automation for infrastructure and deployment scripts
  • Technical Leads and Engineering Managers exploring AI-assisted development for team productivity
  • AI enthusiasts and developers curious about integrating AI into their coding practices
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  • Overview of GitHub Copilot and its AI technology
  • Key features and benefits
  • Setting up GitHub Copilot in Visual Studio Code
  • Installing Copilot in your IDE
  • First steps: Initial configurations and preferences
  • Exploring the basic user interface and capabilities
  • Writing functions and classes with Copilot
  • Best practices for code documentation and comments
  • Handling repetitive tasks and generating boilerplate code
  • How Copilot adapts to different languages (Python, JavaScript, etc.)
  • Practical use in existing projects and legacy codebases
  • Optimizing Copilot for language-specific tasks
  • Personalizing Copilot’s settings for your workflow
  • Extending Copilot with plugins and additional integrations
  • Advanced prompts for tailored code suggestions
  • Managing security risks and preventing common issues
  • Ethical implications of AI-assisted code generation
  • Ensuring data privacy and code accuracy
  • Using Copilot in web development, DevOps, and data science projects
  • Practical applications in automation and infrastructure scripts
  • AI-assisted debugging and testing
  • Lab 1: Building a simple web application with Copilot
  • Lab 2: Refactoring a large codebase using Copilot’s suggestions
  • Lab 3: Debugging and testing with Copilot’s help
  • Crafting effective prompts for improved suggestions
  • Avoiding pitfalls and maximizing productivity
  • Collaborating with Copilot in team environments
  • Emerging trends in AI-driven development tools
  • Preparing for the evolving landscape of software development
  • Next steps: Further learning and exploring additional AI tools
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  • Basic knowledge of programming languages (e.g., Python, JavaScript, Java)
  • Familiarity with Git and GitHub workflows
  • Familiarity with modern IDEs such as VSCode, IntelliJ, or eclipse

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