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Duration 21 hours
Course Outline
Introduction to Generative AI in Software Engineering
- Foundations of Generative AI
- The strategic role of AI within the SDLC
- Survey of AI-driven development utilities
AI-Enhanced Coding
- Leveraging predictive coding capabilities
- Utilizing code generation and autocompletion utilities
- Refining code quality through AI-driven insights
Intelligent Debugging
- Automated detection of errors
- Integrating AI into static code analysis
- Supporting dynamic analysis with AI
AI in Code Review Processes
- Streamlining code review workflows
- Generating optimization suggestions via AI
- Maintaining code standards with AI assistance
Root Cause Analysis via AI
- Adopting a data-centric approach to problem resolution
- Using AI algorithms to pinpoint issues
- Applying predictive analytics to prevent future errors
Case Studies
- Real-world applications of AI within the SDLC
- Analyzing success stories and key takeaways
- Exploring emerging trends in AI for software development
Practical Workshops
- Interactive sessions utilizing AI coding tools
- Collaborative projects focused on AI-assisted debugging
- Conducting peer reviews using AI-generated feedback
Ethics and Best Practices
- Responsible use of AI in software engineering
- Best practices for seamless AI integration into the SDLC
- Balancing human expertise with AI capabilities
Conclusion and Future Directions
Requirements
- A solid foundation in fundamental software development principles
- Practical experience with at least one programming language
- Comfort with standard software development tools and environments
Target Audience
- Software developers
- Technical team leads
- Product managers
Testimonials (1)
I like hands-on experience and engaging audience with content. I also really like that trainer is such a passionate person about technology. He had good energy.