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Course Outline
AI in the Requirements and Planning Phase
- Leveraging NLP and LLMs for requirement analysis
- Translating stakeholder input into epics and user stories
- Using AI tools to refine stories and generate acceptance criteria
AI-Augmented Design and Architecture
- Using AI to model system components and dependencies
- Generating architecture diagrams and receiving UML suggestions
- Validating designs through prompt-based system reasoning
AI-Enhanced Development Workflows
- AI-assisted code generation and creating boilerplate scaffolding
- Refactoring code and improving performance with LLMs
- Integrating AI tools into IDEs (e.g., Copilot, Tabnine, CodeWhisperer)
Testing with AI
- Generating unit and integration tests using AI models
- Conducting regression analysis and test maintenance with AI assistance
- Generating exploratory and boundary cases with AI
Documentation, Review, and Knowledge Sharing
- Automatically generating documentation from code and APIs
- Automating code reviews using AI prompts and checklists
- Building knowledge bases and FAQs with conversational AI
AI in CI/CD and Deployment Automation
- Optimizing pipelines and conducting risk-based testing with AI
- Receiving intelligent suggestions for canary releases and rollbacks
- Utilizing AI for deployment verification and post-deployment analysis
Governance, Ethics, and Implementation Strategy
- Ensuring responsible AI usage and mitigating bias in generated code
- Auditing and maintaining compliance within AI-assisted workflows
- Developing a roadmap for phased AI adoption across the SDLC
Summary and Next Steps
Requirements
- A foundational understanding of software development lifecycle concepts
- Experience in software architecture or team leadership
- Familiarity with DevOps methodologies, agile practices, or SDLC tooling
Target Audience
- Software architects
- Development leads
- Engineering managers
14 Hours
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