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Duration 14 hours
Course Outline
Overview of GitHub Copilot
- Defining GitHub Copilot and its underlying mechanisms
- Reviewing compatible environments and IDE integrations
- Identifying key use cases for developers and DevOps experts
Initial Setup and Interaction with Copilot
- Activating Copilot within Visual Studio Code
- Crafting effective prompts to elicit useful code suggestions
- Interpreting and refining code generated by Copilot
Applying Copilot to DevOps Responsibilities
- Creating YAML configurations for CI/CD workflows
- Developing GitHub Actions with the aid of Copilot
- Streamlining testing, linting, and deployment pipelines through automation
Shell Scripting and Infrastructure Automation
- Employing Copilot to draft and enhance shell scripts
- Requesting specific snippets for Dockerfiles, Terraform, or Kubernetes configurations
- Verifying the accuracy and functionality of generated automation scripts
Enhancing Productivity via AI Support
- Minimizing boilerplate code and routine tasks
- Increasing workflow speed during agile sprints with Copilot
- Integrating Copilot with GitHub CLI and terminal-based workflows
Constraints, Ethics, and Industry Standards
- Recognizing the scope and boundaries of Copilot’s capabilities
- Addressing security issues and intellectual property implications
- Adopting best practices for reviewing AI-generated code
Practical Projects and Scenario-Based Learning
- Automating CI/CD workflows for a web application
- Creating reusable templates for GitHub Actions
- Facilitating team collaboration using Copilot across multiple repositories
Recap and Future Directions
Requirements
- A foundational grasp of core software development principles
- Proficiency with Git or other version control systems
- Introductory experience with YAML, shell scripting, or CI/CD tools
Target Audience
- Developers seeking to elevate their DevOps efficiency
- Novices in DevOps and enthusiasts of automation technologies
- Agile team members looking to integrate AI support into 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
