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Duration 14 hours
Course Outline
Overview of GitHub Copilot
- Defining GitHub Copilot and explaining its operational mechanics
- Identifying supported environments and integration points within IDEs
- Exploring specific use cases for both developers and DevOps specialists
Initial Setup with Copilot
- Activating Copilot within Visual Studio Code
- Crafting prompts to elicit valuable code suggestions from Copilot
- Interpreting and refining the code generated by Copilot
Applying Copilot to DevOps Workflows
- Creating YAML configurations tailored for CI/CD processes
- Developing GitHub Actions with the assistance of Copilot
- Streamlining testing, linting, and deployment pipeline automation
Shell Scripting and Infrastructure Automation
- Employing Copilot to draft and enhance shell scripts
- Requesting snippets for Dockerfiles, Terraform modules, or Kubernetes configurations via Copilot
- Verifying and validating automated scripts generated by the AI
Enhancing Productivity through AI Support
- Minimizing the need for boilerplate code and repetitive manual tasks
- Accelerating work output within agile sprint cycles using Copilot
- Integrating Copilot with GitHub CLI and terminal-based workflows
Boundaries, Ethics, and Professional Standards
- Recognizing the functional scope and limitations of Copilot
- Addressing security implications and intellectual property concerns
- Adopting best practices for reviewing AI-generated code
Practical Projects and Real-World Applications
- Automating CI/CD workflows for a sample web application
- Developing reusable GitHub Action templates
- Facilitating team collaboration by using Copilot across multiple repositories
Conclusion and Future Pathways
Requirements
- A solid grasp of fundamental software development principles
- Proficiency with Git or other version control systems
- Foundational experience with YAML, shell scripting, or CI/CD platforms
Target Audience
- Software developers aiming to elevate their DevOps efficiency
- Entry-level DevOps engineers and enthusiasts of automation technologies
- Agile team members seeking 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
