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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 options
- Practical use cases for developers and DevOps professionals
Getting Started with Copilot
- Enabling Copilot in Visual Studio Code
- Crafting prompts to elicit useful code suggestions from Copilot
- Interpreting and refining code generated by Copilot
Leveraging 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
- Employing Copilot to create and optimize shell scripts
- Requesting Dockerfile, Terraform, or Kubernetes configuration snippets from Copilot
- Validating the accuracy of generated automation scripts
Enhancing Productivity with AI Assistance
- Minimizing boilerplate and repetitive coding tasks
- Accelerating work within agile sprints using Copilot
- Integrating Copilot with GitHub CLI and terminal-based workflows
Limitations, Ethics, and Best Practices
- Understanding the scope and boundaries of Copilot's capabilities
- Addressing security concerns and intellectual property considerations
- Adopting best practices for reviewing AI-generated code
Project Exercises and Real-World Scenarios
- Automating CI/CD workflows for a web application
- Creating reusable GitHub Actions templates
- Facilitating team collaboration using Copilot across multiple repositories
Summary and Next Steps
Requirements
- A foundational understanding of basic software development concepts
- Familiarity with Git or standard version control workflows
- Basic experience working with YAML, shell scripting, or CI/CD tools
Target Audience
- Developers seeking to enhance DevOps productivity
- DevOps newcomers and automation enthusiasts
- Agile team members looking for AI assistance 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
