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Duration 14 hours
Course Outline
Integrating AI in Requirements and Planning
- Applying NLP and LLMs for detailed requirement analysis
- Translating stakeholder feedback into epics and user stories
- Employing AI tools to refine stories and generate acceptance criteria
AI-Supported Design and Architecture
- Leveraging AI to model system components and their dependencies
- Creating architecture diagrams and suggesting UML structures
- Validating designs through prompt-based system reasoning
AI-Optimized Development Workflows
- Assisting code generation and boilerplate scaffolding with AI
- Refactoring code and improving performance using LLMs
- Embedding AI tools into IDEs (such as Copilot, Tabnine, CodeWhisperer)
AI-Assisted Testing
- Creating unit and integration tests with AI models
- Facilitating regression analysis and test maintenance with AI assistance
- Generating exploratory and boundary cases using AI
Documentation, Review, and Knowledge Dissemination
- Auto-generating documentation from code and APIs
- Automating code reviews via AI prompts and checklists
- Developing knowledge bases and FAQs using conversational AI
AI in CI/CD and Deployment Automation
- Optimizing pipelines and implementing risk-based testing with AI
- Suggesting intelligent canary releases and rollbacks
- Utilizing AI for deployment verification and post-deployment analysis
Governance, Ethics, and Adoption Strategy
- Promoting responsible AI use and mitigating bias in generated code
- Ensuring auditing and compliance in AI-assisted workflows
- Formulating a roadmap for phased AI adoption across the SDLC
Conclusion and Future Directions
Requirements
- A solid grasp of software development lifecycle concepts
- Background experience in software architecture or leading development teams
- Familiarity with DevOps, agile methodologies, or SDLC tooling
Target Audience
- Software architects
- Development leads
- Engineering managers
Testimonials (2)
The session was highly interactive and applicable to the business.
Jorge Boscan - Chevron Global Technology Services Company
Course - Advanced GitHub Copilot & AI for Projects and Infrastructure
Machine Translated
That i gained a knowledge regarding streamlit library from python and for sure i'll try to use it to improve applications in my team which are made in R shiny
