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Course Outline
Introduction to Generative AI in Software Engineering
- Core concepts of Generative AI
- Survey of AI-powered development utilities
AI-Enhanced Coding
- Automatic code generation and smart autocompletion
AI-Powered Debugging
- Automated identification of errors
- AI applications in static code evaluation
- AI-assisted dynamic analysis
AI in Code Inspection
- Streamlining code review workflows
- AI-driven recommendations for code efficiency
AI for Root Cause Analysis
- Data-centric strategies for troubleshooting
- Using AI algorithms to pinpoint defects
Case Studies
- Practical applications of AI within the SDLC
- Insights from successful implementations
Practical Workshops
- Interactive use of AI coding platforms
- Collaborative projects focusing on AI-assisted debugging
Ethical Frameworks and Best Practices
Recap and Future Directions
Requirements
- Foundational knowledge of core software engineering principles
- Practical experience with at least one programming language
- Proficiency with standard development tools and environments
Target Audience
- Software engineers and developers
- Technical leads and team managers
- Product managers
21 Hours
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.
