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Duration 14 hours
Course Outline
Integrating AI into the Requirements and Planning Phase
- Applying NLP and LLMs for in-depth requirement analysis.
- Translating stakeholder feedback into epics and user stories.
- Leveraging AI tools to refine stories and generate acceptance criteria.
AI-Augmented Design and Architecture
- Using AI to model system components and their interdependencies.
- Creating architecture diagrams and suggesting UML structures.
- Validating designs through prompt-based system reasoning.
AI-Enhanced Development Workflows
- Utilizing AI-assisted code generation and boilerplate scaffolding.
- Refactoring code and improving performance with the help of LLMs.
- Embedding AI tools directly into IDEs (such as Copilot, Tabnine, and CodeWhisperer).
AI-Driven Testing
- Generating unit and integration tests using AI models.
- Facilitating regression analysis and test maintenance with AI assistance.
- Producing exploratory and boundary case scenarios with AI.
Documentation, Review, and Knowledge Dissemination
- Automatically generating documentation from code and APIs.
- Automating code reviews using AI prompts and checklists.
- Developing knowledge bases and FAQs via conversational AI.
AI in CI/CD and Deployment Automation
- Optimizing pipelines and conducting risk-based testing with AI enhancements.
- Offering intelligent suggestions for canary releases and rollbacks.
- Employing AI for deployment verification and post-deployment analysis.
Governance, Ethics, and Implementation Strategy
- Ensuring responsible AI usage and mitigating bias in generated code.
- Maintaining auditing and compliance standards in AI-assisted workflows.
- Developing a roadmap for the phased adoption of AI across the SDLC.
Conclusion and Future Directions
Requirements
- A solid grasp of software development lifecycle concepts.
- Background experience in software architecture or team leadership.
- Knowledge of DevOps, agile methodologies, or SDLC-related tooling.
Target Audience
- Software architects.
- Development leads.
- Engineering managers.
Testimonials (1)
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
