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GitHub Copilot (GH-300)
Code:
GH-300
Duration:
1 Day
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$675
USD
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This course explores the use of AI in the context of GitHub Copilot, a generative AI tool for developers. It equips users with the knowledge and skills to use Copilot effectively while mitigating potential ethical and operational risks associated with AI usage.
This course is available in the following formats:
Duration: 1 Day
Duration: 1 Day
|
Delivery Format: Virtual Classroom
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$ 675 |
|
|
Delivery Format: Virtual Classroom
|
$ 675 |
|
|
Delivery Format: Virtual Classroom
|
$ 675 |
Module 1: GitHub Copilot Fundamentals Part 1
- Responsible AI with GitHub Copilot
- Introduction to GitHub Copilot
- Introduction to prompt engineering with GitHub Copilot
- Using advanced GitHub Copilot features
- GitHub Copilot Across Environments: IDE, Chat, and Command Line Techniques
- Management and customization considerations with GitHub Copilot
Module 2:GitHub Copilot Fundamentals Part 2
- Developer use cases for AI with GitHub Copilot
- Develop unit tests using GitHub Copilot tools
- Introduction to GitHub Copilot Business
- Introduction to GitHub Copilot Enterprise
- Using GitHub Copilot with JavaScript
- Using GitHub Copilot with Python
Module 1: GitHub Copilot Fundamentals Part 1
- Responsible AI with GitHub Copilot
- Introduction to GitHub Copilot
- Introduction to prompt engineering with GitHub Copilot
- Using advanced GitHub Copilot features
- GitHub Copilot Across Environments: IDE, Chat, and Command Line Techniques
- Management and customization considerations with GitHub Copilot
Module 2:GitHub Copilot Fundamentals Part 2
- Developer use cases for AI with GitHub Copilot
- Develop unit tests using GitHub Copilot tools
- Introduction to GitHub Copilot Business
- Introduction to GitHub Copilot Enterprise
- Using GitHub Copilot with JavaScript
- Using GitHub Copilot with Python
- AI Developers and Engineers: Professionals involved in creating and deploying AI systems who need to understand the ethical implications and governance frameworks.
- Data Scientists and Analysts: Individuals who work with data and AI models, focusing on ensuring transparency, fairness, and accountability in their work.
- Business Leaders and Managers: Decision-makers who oversee AI projects and need to implement responsible AI practices within their organizations.
- Policy Makers and Regulators: Those responsible for creating policies and regulations around AI usage, ensuring that AI systems are developed and used ethically and safely.