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 Duration 21 hours

Course Outline

Foundational Concepts of Generative AI in Software Development

  • Conceptual understanding of Generative AI
  • The function of AI within the SDLC
  • Survey of AI-powered development tools

AI-Supported Coding Practices

  • Predictive coding enabled by AI
  • Utilizing code generation and autocompletion utilities
  • Improving code quality through AI-derived insights

Intelligent Debugging Strategies

  • Automated identification of errors
  • The role of AI in static code analysis
  • Conducting dynamic analysis with AI assistance

AI in the Code Review Process

  • Streamlining code review procedures
  • Leveraging AI for code optimization recommendations
  • Maintaining code standards through AI monitoring

AI-Driven Root Cause Analysis

  • Adopting a data-centric approach to problem resolution
  • Using AI algorithms to pinpoint issues
  • Applying predictive analytics to prevent future errors

Real-World Case Studies

  • Practical examples of AI integration in the SDLC
  • Analysis of success stories and key takeaways
  • Emerging trends in AI for software engineering

Practical Workshop Sessions

  • Interactive exercises utilizing AI coding tools
  • Collaborative projects focused on AI-assisted debugging
  • Peer reviews informed by AI-generated observations

Ethics and Professional Best Practices

  • Ethical deployment of AI in software development
  • Best practices for embedding AI into the SDLC
  • Harmonizing human expertise with AI capabilities

Conclusion and Future Directions

Requirements

  • A solid grasp of fundamental software development principles
  • Practical experience with at least one programming language
  • Proficiency with common software development tools and environments

Target Audience

  • Software developers
  • Technical team leads
  • Product managers

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