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Duration 7 hours
Course Outline
Introduction to AI in Requirements Engineering
- Survey of AI tools relevant to product teams
- Exploring the function of requirements within Agile and Scrum
- Examining the advantages and constraints of AI in requirement capture
Collecting and Structuring Requirements via AI
- AI-driven interview simulations: converting verbal feedback into requirements
- Prompt engineering techniques for clarifying ambiguous statements
- Categorizing requirements into themes and features
Creation of User Stories and Epics
- Transforming plain text into actionable user stories
- Leveraging AI to discern actors, actions, and objectives
- Establishing epics and story hierarchies based on AI recommendations
Drafting Acceptance Criteria and Edge Cases
- Generating testable Given-When-Then criteria
- Detecting exception paths and boundary conditions with AI support
- Assessing AI outputs for clarity and thoroughness
AI-Assisted Refinement and Story Grooming
- Condensing stakeholder meeting notes and discussions
- Dividing and combining stories through guided prompting
- Streamlining backlog refinement using AI assistance
Collaboration and Handover Process
- Distributing AI-generated stories to developers
- Maintaining traceability from feature specification to test case
- Preparing documentation for stakeholder approval
Conclusion and Future Directions
Requirements
- Foundational knowledge of software project lifecycles
- Experience with Agile or Scrum methodologies
- No prior technical expertise is necessary
Intended Audience
- Product owners
- Business analysts
- Scrum masters
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
