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Course Outline
Getting Started with AI Coding Assistants
- Defining AI coding assistants.
- The history and evolution of AI in software development.
- Advantages and constraints of AI coding assistants.
Key Technologies Powering AI Coding Assistants
- Overview of machine learning and natural language processing.
- Introduction to code generation algorithms.
- Integrating AI with development tools.
Investigating Leading AI Coding Assistant Tools
- Overview of tools such as GitHub Copilot and IntelliCode.
- Practical sessions focusing on core features.
- Comparative analysis of various tools.
Integrating into Basic Workflows
- Configuring an AI coding assistant within an IDE.
- Leveraging AI assistants for simple coding tasks.
- Tailoring the assistant to specific requirements.
Ethical Considerations and Responsible Use
- Understanding bias and fairness in AI tools.
- Fundamental guidelines for responsible usage.
- Privacy and security implications.
Project Work
- Applying an AI coding assistant to a small-scale project.
- Peer review and constructive feedback.
- Discussion on project enhancements and key takeaways.
Summary and Next Steps
Requirements
- Foundational knowledge of software development
- Proficiency in at least one programming language (e.g., Python, JavaScript)
Target Audience
- Software developers
- Product managers
- Technical team leads
14 Hours
Testimonials (1)
The way you use the copilot, more rule more close to what you need.
