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Course Outline
Introduction to AI Coding Assistants
- Overview of AI in software engineering
- History and evolution of AI coding assistants
- Key features and capabilities
Technologies Behind AI Coding Assistants
- Machine learning and natural language processing
- Code analysis and generation algorithms
- Integration with development environments
Popular AI Coding Assistant Tools
- Comparative study of different tools
- Hands-on sessions with tools like GitHub Copilot, IntelliCode, etc.
- Community contributions and extensions
Best Practices and Workflow Integration
- Incorporating AI assistants into daily workflows
- Collaboration with AI assistants
- Customizing and training your AI assistant
Case Studies and Real-World Applications
- Success stories of AI assistants in development projects
- Limitations and challenges
- Future trends and developments
Ethical Considerations and Responsible Use
- Addressing bias and fairness in AI tools
- Intellectual property and code ownership
- Privacy and security implications
Project Work
- Developing a mini project with the aid of an AI coding assistant
- Peer reviews and feedback sessions
Summary and Next Steps
Requirements
- An understanding of basic software development concepts
- Experience with a programming language (e.g., Python, JavaScript)
- Familiarity with integrated development environments (IDEs)
Audience
- Software developers
- Technical team leads
- Product managers
14 Hours
Testimonials (1)
Lecturer's knowledge in advanced usage of copilot & Sufficient and efficient practical session