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
 7 Hours

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