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Duration 14 hours
Course Outline
Introduction to AI-Powered Coding Helpers
- Defining AI coding assistants. <\/li>
- The history and progression of AI in software engineering. <\/li>
- Advantages and constraints of using AI coding assistants. <\/li>
Key Technologies Powering AI Coding Assistants
- Overview of machine learning and natural language processing. <\/li>
- Introduction to code generation algorithms. <\/li>
- How AI integrates with development tools. <\/li>
Examining Popular AI Coding Assistant Platforms
- Overview of prominent tools such as GitHub Copilot and IntelliCode. <\/li>
- Practical sessions focusing on core features. <\/li>
- Comparative analysis of various tools. <\/li>
Integrating into Basic Workflows
- Configuring an AI coding assistant within an IDE. <\/li>
- Leveraging AI assistants for straightforward coding tasks. <\/li>
- Customizing the assistant to meet specific requirements. <\/li>
Ethical Considerations and Responsible Usage
- Comprehending bias and fairness within AI tools. <\/li>
- Fundamental guidelines for ethical deployment. <\/li>
- Addressing privacy and security concerns. <\/li>
Hands-on Project
- Applying an AI coding assistant to a small-scale project. <\/li>
- Peer review and constructive feedback. <\/li>
- Discussion on potential improvements and key takeaways. <\/li>
Summary and Future Steps
Requirements
- Foundational knowledge of software development <\/li>
- Familiarity with at least one programming language (such as Python or JavaScript) <\/li>
Target Audience<\/strong>
- Software developers <\/li>
- Product managers <\/li>
- Technical team leads <\/li>
Testimonials (1)
The way you use the copilot, more rule more close to what you need.
