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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 integration details
- Specific use cases for developers and DevOps specialists
Getting Started with Copilot
- Activating Copilot within Visual Studio Code
- Crafting effective prompts to elicit valuable code suggestions
- Analyzing and refining code generated by Copilot
Applying Copilot to DevOps Tasks
- Creating YAML configurations for CI/CD workflows
- Developing GitHub Actions with Copilot assistance
- Automating pipelines for testing, linting, and deployment
Shell Scripting and Infrastructure Automation
- Employing Copilot to draft and optimize shell scripts
- Requesting code snippets for Dockerfiles, Terraform, or Kubernetes configurations
- Validating the integrity of generated automation scripts
Enhancing Productivity via AI
- Minimizing boilerplate and repetitive manual tasks
- Accelerating work cycles within agile sprints using Copilot
- Integrating Copilot with GitHub CLI and terminal-based workflows
Limitations, Ethics, and Best Practices
- Defining the scope and boundaries of Copilot's capabilities
- Addressing security risks and intellectual property implications
- Best practices for auditing AI-generated code
Practical Exercises and Real-World Applications
- Automating CI/CD workflows for web applications
- Constructing reusable GitHub Action templates
- Facilitating team collaboration using Copilot across multiple repositories
Wrap-up and Future Directions
Requirements
- A solid grasp of fundamental software development principles
- Proficiency with Git or general version control workflows
- Foundational experience with YAML, shell scripting, or CI/CD tools
Target Audience
- Developers aiming to enhance their DevOps productivity
- Newcomers to DevOps and enthusiasts of automation
- Agile team members seeking AI integration in their daily 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
