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Course Outline

Overview of Artificial Intelligence Coding Assistants

  • Definition and function of AI coding assistants
  • Historical context and development of AI in software engineering
  • Advantages and constraints associated with AI coding assistants for government

Fundamental Technologies Supporting AI Coding Assistants

  • Summary of machine learning principles and natural language processing capabilities
  • Explanation of code generation methodologies
  • Incorporation of AI technologies into development environments

Examination of Prominent AI Coding Assistant Platforms

  • Survey of widely used tools such as GitHub Copilot and IntelliCode
  • Practical application exercises focusing on core features
  • Comparative evaluation of various tool capabilities

Integration into Standard Development Workflows

  • Configuration of AI coding assistants within Integrated Development Environments (IDEs)
  • Utilization of AI assistance for routine programming tasks
  • Adaptation of assistant settings to meet specific organizational requirements

Ethical Standards and Responsible Deployment

  • Assessment of bias mitigation and fairness in AI systems
  • Foundational guidelines for the responsible use of AI tools
  • Identification of privacy and security implications

Capstone Project Application

  • Implementation of an AI coding assistant in a designated project scope
  • Structured peer review and constructive feedback processes
  • Analysis of project outcomes, improvements, and key learnings

Conclusion and Future Directions

Requirements

  • Fundamental knowledge of software engineering principles
  • Proficiency in at least one programming language (e.g., Python, JavaScript) suitable for government applications

Audience

  • Software engineers
  • Product managers
  • Technical team leads
 14 Hours

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