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Duration 14 hours
Course Outline
AI in Requirements and Planning
- Leveraging NLP and LLMs for in-depth requirement analysis.
- Translating stakeholder inputs into epics and user stories.
- Employing AI tools to refine stories and generate acceptance criteria.
AI-Augmented Design and Architecture
- Modeling system components and dependencies with AI assistance.
- Creating architecture diagrams and suggesting UML structures.
- Validating designs through prompt-based system reasoning.
AI-Enhanced Development Workflows
- Assisting code generation and scaffolding boilerplate code with AI.
- Refactoring code and boosting performance using LLMs.
- Integrating AI tools into IDEs (such as Copilot, Tabnine, and CodeWhisperer).
Testing with AI
- Creating unit and integration tests using AI models.
- Managing regression analysis and test maintenance with AI support.
- Generating exploratory and boundary cases using 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 performing risk-based testing with AI.
- Providing 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.
- Maintaining auditing and compliance standards in AI-assisted workflows.
- Developing a roadmap for phased AI adoption across the SDLC.
Summary and Next Steps
Requirements
- A solid grasp of software development lifecycle principles.
- Practical experience in software architecture or leading development teams.
- Familiarity with 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
