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Duration 14 hours
Course Outline
Introduction to GitHub Copilot
- Defining GitHub Copilot and exploring its operational mechanics.
- Reviewing supported environments and IDE integrations.
- Identifying key use cases for both developers and DevOps professionals.
Getting Started with Copilot
- Activating Copilot within Visual Studio Code.
- Crafting effective prompts to elicit useful code suggestions.
- Evaluating and refining code generated by Copilot for optimal quality.
Applying Copilot to DevOps Tasks
- Generating robust YAML configurations for CI/CD workflows.
- Developing GitHub Actions with the support of Copilot.
- Automating complex testing, linting, and deployment pipelines.
Shell Scripting and Infrastructure Automation
- Leveraging Copilot to draft and optimize shell scripts.
- Prompting Copilot for specific snippets such as Dockerfiles, Terraform code, or Kubernetes configurations.
- Rigorous validation of generated automation scripts to ensure reliability.
Enhancing Productivity with AI Assistance
- Minimizing the impact of boilerplate code and repetitive tasks.
- Accelerating workflow efficiency during agile sprints using Copilot.
- Integrating Copilot with GitHub CLI and terminal-based workflows.
Navigating Limitations, Ethics, and Best Practices
- Gaining a clear understanding of Copilot's scope and functional boundaries.
- Addressing security implications and intellectual property considerations.
- Adopting best practices for the critical review of AI-generated code.
Project Exercises and Real-World Applications
- Automating CI/CD workflows specifically for web applications.
- Creating reusable GitHub Actions templates for consistent deployments.
- Facilitating team collaboration by using Copilot across multiple repositories.
Course Summary and Future Steps
Requirements
- A foundational grasp of core software development principles.
- Proficiency with Git and general version control workflows.
- Foundational experience with YAML syntax, shell scripting, or CI/CD tooling.
Target Audience
- Developers aiming to enhance their DevOps productivity through AI assistance.
- DevOps professionals and automation enthusiasts starting their journey.
- 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
