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Duration 14 hours
Course Outline
Introduction to GitHub Copilot
- Overview of GitHub Copilot and its operational mechanisms
- Supported environments and IDE integration
- Key use cases for developers and DevOps professionals
Getting Started with Copilot
- Enabling Copilot in Visual Studio Code
- Crafting effective prompts for useful code suggestions
- Reviewing and refining Copilot-generated code
Using Copilot for DevOps Tasks
- Generating YAML configurations for CI/CD workflows
- Developing GitHub Actions with Copilot assistance
- Automating testing, linting, and deployment pipelines
Shell Scripting and Infrastructure Automation
- Utilising Copilot to write and enhance shell scripts
- Prompting Copilot for Dockerfile, Terraform, or Kubernetes configuration snippets
- Validating generated automation scripts
Productivity Boost with AI Assistance
- Minimising boilerplate and repetitive tasks
- Improving velocity with Copilot during agile sprints
- Integrating Copilot with GitHub CLI and terminal workflows
Limitations, Ethics, and Best Practices
- Understanding the scope and boundaries of Copilot
- Addressing security concerns and intellectual property considerations
- Best practices for reviewing AI-generated code
Project Exercises and Real-World Scenarios
- CI/CD workflow automation for a web application
- Creating reusable GitHub Actions templates
- Team collaboration using Copilot across repositories
Summary and Next Steps
Requirements
- A solid understanding of fundamental software development concepts
- Familiarity with Git or version control workflows
- Basic experience with YAML, shell scripting, or CI/CD tools
Audience
- Developers aiming to enhance DevOps productivity
- DevOps beginners and automation enthusiasts
- Agile team members seeking AI support in their workflows
Testimonials (1)
That i gained a knowledge regarding streamlit library from python and for sure i'll try to use it to improve applications in my team which are made in R shiny
