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Course Outline

Fundamentals of Generative AI in Software Engineering

  • Core concepts of Generative AI
  • The impact of AI on the SDLC
  • Survey of AI-powered development tools

AI-Enhanced Coding

  • Predictive coding capabilities
  • Leveraging code generation and autocomplete features
  • Improving code quality through AI-driven insights

Intelligent Debugging

  • Automation of error detection
  • AI applications in static code analysis
  • Dynamic analysis supported by AI

AI in Code Review

  • Streamlining code review workflows
  • AI-generated suggestions for code optimization
  • Maintaining coding standards with AI assistance

Root Cause Analysis via AI

  • Data-centric problem-solving strategies
  • AI algorithms for pinpointing issues
  • Using predictive analytics to avert future errors

Case Studies

  • Practical examples of AI integration in the SDLC
  • Success narratives and key takeaways
  • Emerging trends in AI for software development

Practical Workshops

  • Interactive sessions utilizing AI coding tools
  • Collaborative projects focusing on AI-assisted debugging
  • Peer reviews based on AI-generated insights

Ethics and Best Practices

  • Responsible use of AI in software engineering
  • Best practices for AI integration into the SDLC
  • Striking a balance between human expertise and AI capabilities

Recap and Future Directions

Requirements

  • A solid foundation in core software development principles
  • Practical experience with at least one programming language
  • Proficiency with standard software development tools and environments

Target Audience

  • Software Developers
  • Technical Team Leads
  • Product Managers
 21 Hours

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