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Course Outline

Introduction to AI Coding Assistants

  • Defining AI coding assistants
  • The historical progression of AI within software development
  • Key advantages and inherent limitations

Underlying Technologies in AI Coding Assistants

  • Foundations of machine learning and natural language processing
  • Fundamentals of code generation algorithms
  • Integrating AI capabilities with existing development tools

Surveying Leading AI Coding Assistant Tools

  • Reviewing prominent tools such as GitHub Copilot and IntelliCode
  • Practical sessions exploring core functionalities
  • Comparative evaluation of different toolsets

Integrating into Basic Workflows

  • Configuring AI coding assistants within an IDE
  • Leveraging AI support for straightforward coding challenges
  • Tailoring assistant settings to specific project needs

Ethical Implications and Responsible Usage

  • Addressing bias and fairness issues in AI models
  • Establishing guidelines for ethical and responsible application
  • Managing privacy and security risks

Practical Project Work

  • Implementing AI coding assistants in a small-scale project
  • Conducting peer reviews and exchanging feedback
  • Reflecting on improvements and key takeaways

Conclusion and Future Directions

Requirements

  • Foundational knowledge of software development
  • Practical experience with at least one programming language (such as Python or JavaScript)

Target Audience

  • Software developers
  • Product managers
  • Technical team leaders
 14 Hours

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