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Course Outline

Introduction to Generative AI in Software Development

  • Understanding Generative AI.
  • The role of AI in the SDLC.
  • Overview of AI-driven development tools.

AI-Assisted Coding

  • Predictive coding with AI.
  • Code generation and autocompletion tools.
  • Enhancing code quality with AI insights.

Debugging with AI

  • Automated error detection.
  • AI in static code analysis.
  • Dynamic analysis with AI support.

AI in Code Reviews

  • Automating code review processes.
  • AI for code optimization suggestions.
  • Ensuring code standards with AI.

Root Cause Analysis with AI

  • Data-driven approach to problem-solving.
  • AI algorithms for identifying issues.
  • Predictive analytics for preventing future errors.

Case Studies

  • Real-world examples of AI in the SDLC.
  • Success stories and lessons learned.
  • Future trends in AI for software development.

Hands-On Workshops

  • Interactive sessions with AI coding tools.
  • Group projects on AI-assisted debugging.
  • Peer reviews using AI-generated insights.

Ethical Considerations and Best Practices

  • Ethical use of AI in software development.
  • Best practices for integrating AI into the SDLC.
  • Balancing human expertise with AI capabilities.

Summary and Next Steps

Requirements

  • Understanding of basic software development concepts.
  • Experience with any programming language.
  • Familiarity with software development tools and environments.

Audience

  • Software developers.
  • Technical team leads.
  • Product managers.
 21 Hours

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