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Duration 7 hours
Course Outline
Intro to AI in Requirements Engineering
- Survey of AI tools available to product teams
- The function of requirements within Agile and Scrum frameworks
- Advantages and constraints of AI in requirement capture
Collecting and Organizing Requirements via AI
- AI-driven interview simulations: converting spoken input into formal requirements
- Prompting methods to resolve ambiguous statements
- Grouping requirements into thematic areas and features
Creating User Stories and Epics
- Translating raw text into actionable user stories
- Utilizing AI to pinpoint actors, actions, and objectives
- Building epics and story hierarchies based on AI insights
Drafting Acceptance Criteria and Edge Cases
- Producing Given-When-Then testable conditions
- Detecting exception paths and boundary conditions with AI aid
- Evaluating AI-generated outputs for precision and thoroughness
Refining and Grooming Stories with AI
- Condensing stakeholder meeting notes and discussions
- Dividing or consolidating stories guided by specific prompts
- Streamlining backlog refinement through AI assistance
Team Collaboration and Handover
- Distributing AI-crafted stories to development teams
- Maintaining traceability from features to test cases
- Preparing documentation for stakeholder approval
Recap and Forward Planning
Requirements
- Foundational knowledge of software project lifecycles
- Basic familiarity with Agile or Scrum methodologies
- No prior technical experience is necessary
Intended Participants
- 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