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Course Outline

Introduction to AI Coding Assistants <\/p>

  • What are AI coding assistants? <\/li>
  • History and evolution of AI in software development <\/li>
  • Benefits and limitations of AI coding assistants <\/li> <\/ul>

    Core Technologies Behind AI Coding Assistants <\/p>

    • Overview of machine learning and natural language processing <\/li>
    • Introduction to code generation algorithms <\/li>
    • Integration of AI with development tools <\/li> <\/ul>

      Exploring Popular AI Coding Assistant Tools <\/p>

      • Overview of tools like GitHub Copilot, IntelliCode <\/li>
      • Hands-on sessions with basic features <\/li>
      • Comparative analysis of different tools <\/li> <\/ul>

        Basic Workflow Integration <\/p>

        • Setting up an AI coding assistant in an IDE <\/li>
        • Using AI assistants for simple coding tasks <\/li>
        • Customizing the assistant for specific needs <\/li> <\/ul>

          Ethical Considerations and Responsible Use <\/p>

          • Understanding bias and fairness in AI tools <\/li>
          • Basic guidelines for responsible use <\/li>
          • Privacy and security concerns <\/li> <\/ul>

            Project Work <\/p>

            • Applying an AI coding assistant to a small project <\/li>
            • Peer review and feedback <\/li>
            • Discussion on project improvements and lessons learned <\/li> <\/ul>

              Summary and Next Steps <\/ul>

Requirements

  • Basic understanding of software development <\/li>
  • Experience with at least one programming language (e.g., Python, JavaScript) <\/li> <\/ul>

    Audience<\/strong> <\/p>

    • Software developers <\/li>
    • Product managers <\/li>
    • Technical team leads <\/li> <\/ul>
 14 Hours

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