Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Duration 14 hours
Course Outline
Foundational Overview of GitHub Copilot
- Defining GitHub Copilot and its operational mechanisms.
- Identifying supported environments and IDE integration points.
- Exploring specific use cases for both software developers and DevOps specialists.
Initial Setup and Copilot Navigation
- Activating Copilot features within Visual Studio Code.
- Crafting effective prompts to elicit valuable code suggestions.
- Evaluating and refining code generated by Copilot.
Applying Copilot to DevOps Responsibilities
- Creating YAML configurations tailored for CI/CD workflows.
- Developing GitHub Actions with the assistance of Copilot.
- Streamlining pipelines for testing, linting, and deployment automation.
Shell Scripting and Infrastructure Management
- Leveraging Copilot to compose and enhance shell scripts.
- Requesting specific snippets for Dockerfiles, Terraform, or Kubernetes configurations.
- Verifying the accuracy and security of generated automation scripts.
Enhancing Productivity Through AI Support
- Minimizing boilerplate code and reducing repetitive manual tasks.
- Achieving greater velocity within agile sprint cycles using Copilot.
- Integrating Copilot with GitHub CLI and terminal-based workflows.
Ethical Considerations and Operational Best Practices
- Recognizing the functional scope and boundaries of Copilot.
- Addressing security implications and intellectual property considerations.
- Establishing robust review processes for AI-generated code.
Practical Projects and Scenario-Based Learning
- Automating CI/CD workflows for a sample web application.
- Designing and writing reusable GitHub Action templates.
- Facilitating team collaboration using Copilot across multiple repositories.
Course Conclusion and Future Directions
Requirements
- A solid grasp of fundamental software development principles.
- Familiarity with Git or other version control systems and workflows.
- Entry-level experience with YAML syntax, shell scripting, or CI/CD platforms.
Target Audience
- Developers aiming to elevate their DevOps output and efficiency.
- Aspiring DevOps engineers and automation-focused professionals.
- Agile team members seeking to integrate AI capabilities 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
