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Course Outline
Introduction to Generative AI in Software Development <\/p>
- Understanding Generative AI <\/li>
- The role of AI in the SDLC <\/li>
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Overview of AI-driven development tools
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AI-Assisted Coding <\/p>
- Predictive coding with AI <\/li>
- Code generation and autocompletion tools <\/li>
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Enhancing code quality with AI insights
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Debugging with AI <\/p>
- Automated error detection <\/li>
- AI in static code analysis <\/li>
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Dynamic analysis with AI support
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AI in Code Reviews <\/p>
- Automating code review processes <\/li>
- AI for code optimization suggestions <\/li>
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Ensuring code standards with AI
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Root Cause Analysis with AI <\/p>
- Data-driven approach to problem-solving <\/li>
- AI algorithms for identifying issues <\/li>
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Predictive analytics for preventing future errors
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Case Studies <\/p>
- Real-world examples of AI in the SDLC <\/li>
- Success stories and lessons learned <\/li>
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Future trends in AI for software development
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Hands-On Workshops <\/p>
- Interactive sessions with AI coding tools <\/li>
- Group projects on AI-assisted debugging <\/li>
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Peer reviews using AI-generated insights
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Ethical Considerations and Best Practices <\/p>
- Ethical use of AI in software development <\/li>
- Best practices for integrating AI into the SDLC <\/li>
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Balancing human expertise with AI capabilities
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Summary and Next Steps <\/p>
Requirements
- A foundational understanding of software development concepts. <\/li>
- Experience with at least one programming language. <\/li>
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Familiarity with software development tools and environments.
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Target Audience<\/strong> <\/p>
- Software developers. <\/li>
- Technical team leads. <\/li>
- Product managers. <\/li> <\/ul>
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.
