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Duration 14 hours
Course Outline
Introduction to GitHub Copilot
- Overview of GitHub Copilot and its operational mechanics
- Compatible environments and IDE integrations
- Key use cases for developers and DevOps specialists
Getting Started with Copilot
- Activating Copilot within Visual Studio Code
- Crafting prompts to elicit effective code suggestions from Copilot
- Analyzing and refining code generated by Copilot
Applying Copilot to DevOps Tasks
- Creating YAML configurations for CI/CD workflows
- Developing GitHub Actions with the assistance of Copilot
- Streamlining testing, linting, and deployment pipelines
Shell Scripting and Infrastructure Automation
- Employing Copilot to author and enhance shell scripts
- Requesting Dockerfile, Terraform, or Kubernetes configuration snippets from Copilot
- Verifying the accuracy of generated automation scripts
Enhancing Productivity with AI Support
- Minimizing boilerplate code and repetitive tasks
- Increasing velocity during agile sprints using Copilot
- Integrating Copilot with GitHub CLI and terminal-based workflows
Limitations, Ethics, and Best Practices
- Recognizing the scope and boundaries of Copilot’s capabilities
- Addressing security risks and intellectual property issues
- Following best practices for reviewing AI-generated code
Project Exercises and Real-World Scenarios
- Automating CI/CD workflows for web applications
- Developing reusable GitHub Action templates
- Facilitating team collaboration using Copilot across multiple repositories
Summary and Future Steps
Requirements
- Fundamental knowledge of software development principles
- Proficiency with Git or version control processes
- Basic familiarity with YAML, shell scripting, or CI/CD tools
Target Audience
- Developers aiming to enhance DevOps efficiency
- DevOps novices and automation enthusiasts
- Agile team members looking to integrate AI support into 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