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Course Outline
AI in the Requirements and Planning Phase
- Applying NLP and LLMs for requirement analysis.
- Transforming stakeholder input into epics and user stories.
- Using AI tools for story refinement and generating acceptance criteria.
AI-Augmented Design and Architecture
- Leveraging AI to model system components and dependencies.
- Generating architecture diagrams and UML suggestions.
- Validating designs through prompt-based system reasoning.
AI-Enhanced Development Workflows
- Utilizing AI-assisted code generation and boilerplate scaffolding.
- Improving code refactoring and performance via LLMs.
- Integrating AI tools into IDEs (e.g., Copilot, Tabnine, CodeWhisperer).
Testing with AI
- Generating unit and integration tests using AI models.
- Performing AI-assisted regression analysis and test maintenance.
- Creating exploratory tests 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.
- Developing knowledge bases and FAQs using conversational AI.
AI in CI/CD and Deployment Automation
- Optimizing pipelines and implementing 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.
- Managing auditing and compliance within AI-assisted workflows.
- Establishing a roadmap for phased AI adoption across the SDLC.
Summary and Next Steps
Requirements
- Fundamental understanding of software development lifecycle concepts.
- Experience in software architecture or team leadership roles.
- 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