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Coding with an AI pair programmer: Getting started with GitHub Copilot
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The explosion of programming languages and frameworks has ironically made development more difficult. Developers need to remember different syntax across different environments, and are finding that a large percentage of code they write is tedious. Acting as an AI pair programmer, GitHub Copilot can help a developer offload those tasks and instead focus on the bigger picture. Let's explore how to get started with GitHub Copilot, its capabilities, and how to make the most out of the tool.
▬▬▬▬▬▬ TIMESTAMPS ⌚ ▬▬▬▬▬▬
00:00 - Introduction to GitHub Copilot
01:30 - GitHub Copilot Mechanics
03:00 - Data Handling in GitHub Copilot
04:33 - Adapting Workflow with Copilot
06:03 - Effective Prompt Crafting
08:37 - GitHub Copilot Coding Demo
10:21 - GitHub Copilot Best Practices
12:08 - Django Modeling with Copilot
14:10 - Fine-Tuning Django Code
16:43 - Naming Conventions for Copilot
19:02 - Django Views Optimization
21:20 - Creating Django Views
23:08 - Using Comments and Examples
25:38 - Refining Code with Copilot
28:08 - Key Takeaways and Practices
29:38 - Conclusion
Stay up-to-date on all things GitHub by connecting with us:
About GitHub
▬▬▬▬▬▬ TIMESTAMPS ⌚ ▬▬▬▬▬▬
00:00 - Introduction to GitHub Copilot
01:30 - GitHub Copilot Mechanics
03:00 - Data Handling in GitHub Copilot
04:33 - Adapting Workflow with Copilot
06:03 - Effective Prompt Crafting
08:37 - GitHub Copilot Coding Demo
10:21 - GitHub Copilot Best Practices
12:08 - Django Modeling with Copilot
14:10 - Fine-Tuning Django Code
16:43 - Naming Conventions for Copilot
19:02 - Django Views Optimization
21:20 - Creating Django Views
23:08 - Using Comments and Examples
25:38 - Refining Code with Copilot
28:08 - Key Takeaways and Practices
29:38 - Conclusion
Stay up-to-date on all things GitHub by connecting with us:
About GitHub
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