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Duration 14 hours
Course Outline
Introduction to GitHub Copilot
- Overview of AI-assisted pair programming
- Understanding the capabilities and boundaries of GitHub Copilot
- The Copilot ecosystem: spanning IDEs, CLI, Pull Requests, and Chat
Getting Started
- Installation and configuration of GitHub Copilot in VS Code, JetBrains, and Neovim
- GitHub authentication and subscription management
- Navigating Copilot settings and user preferences
Using GitHub Copilot Effectively
- Creating code completions, functions, and boilerplate
- Handling multi-line and context-sensitive suggestions
- Refining and customizing Copilot output
- Drafting comments and documentation with Copilot
Copilot Chat and Collaboration Features
- Utilizing Copilot Chat for API discovery and code refactoring
- Debugging and error resolution via Copilot Chat
- Leveraging Copilot in Pull Requests for suggestions and code reviews
Advanced Workflows with Copilot
- Integrating Copilot into command-line interfaces (CLI)
- Applying Copilot in test-driven development contexts
- Combining Copilot with various frameworks and libraries
Responsible and Secure Usage
- Grasping licensing, privacy, and intellectual property implications
- Mitigating risks associated with insecure or biased code
- Best practices for enterprise-wide and team adoption
Best Practices and Case Studies
- Enhancing daily development productivity with Copilot
- Real-world examples of Copilot application across different programming languages
- Insights and success stories from teams utilizing Copilot
Summary and Next Steps
Requirements
- Foundational programming proficiency in at least one language (such as Python, JavaScript, Java, or C#)
- Experience with using an IDE or code editor (e.g., VS Code or JetBrains)
- Basic understanding of Git and GitHub workflows is advantageous
Target Audience
- Developers
- Programmers
- Software engineers
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