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Course Outline

Artificial Intelligence Applications in Requirements and Planning

  • Leveraging natural language processing and large language models for requirement analysis
  • Translating stakeholder inputs into epics and user stories
  • Utilizing AI tools to refine user stories and generate acceptance criteria

AI-Augmented Design and Architecture

  • Employing AI to model system components and dependencies
  • Generating architecture diagrams and Unified Modeling Language (UML) suggestions
  • Validating design decisions through prompt-based system reasoning

AI-Enhanced Development Workflows

  • Supporting code generation and creating boilerplate scaffolding with AI assistance
  • Improving code refactoring and performance using large language models
  • Integrating AI tools into Integrated Development Environments (IDEs), such as Copilot, Tabnine, and CodeWhisperer

Testing with AI

  • Generating unit and integration tests using AI models
  • Facilitating regression analysis and test maintenance through AI assistance
  • Identifying exploratory and boundary cases with AI support

Documentation, Review, and Knowledge Sharing

  • Automatically generating documentation from code and application programming interfaces (APIs)
  • Automating code reviews using AI prompts and checklists
  • Developing knowledge bases and frequently asked questions (FAQs) via conversational AI

AI in Continuous Integration/Continuous Deployment (CI/CD) and Automation

  • Optimizing pipelines and conducting risk-based testing with AI enhancement
  • Providing intelligent suggestions for canary releases and rollback procedures
  • Supporting deployment verification and post-deployment analysis using AI

Governance, Ethics, and Implementation Strategy

  • Ensuring responsible AI usage and mitigating bias in generated code for government applications where appropriate
  • Maintaining auditing standards and compliance within AI-assisted workflows
  • Developing a roadmap for phased AI adoption across the software development life cycle

Summary and Next Steps

Requirements

  • Proficiency in software development lifecycle methodologies
  • Background in software architecture or team leadership roles
  • Knowledge of DevOps principles, agile frameworks, or SDLC tools

Target Audience

  • Software architects
  • Development team leads
  • Engineering management personnel
 14 Hours

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