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Duration 7 hours
Course Outline
Intro to AI in Requirements Engineering
- Overview of AI tools tailored for product teams
- Grasping the function of requirements within Agile and Scrum
- Advantages and constraints of utilizing AI for requirement documentation
Collecting and Structuring Requirements via AI
- Simulating interviews with AI: converting spoken input into requirements
- Prompting strategies to resolve ambiguous statements
- Categorizing requirements into themes and features
Creating User Stories and Epics
- Transforming raw text into actionable user stories
- Employing AI to pinpoint actors, actions, and objectives
- Building epics and story hierarchies based on AI recommendations
Drafting Acceptance Criteria and Edge Cases
- Producing testable Given-When-Then criteria
- Detecting exception paths and boundary conditions using AI
- Evaluating AI outputs for clarity and thoroughness
Refinement and Story Grooming via AI
- Condensing stakeholder meeting notes and records
- Dividing and combining stories with prompt guidance
- Streamlining backlog refinement with AI support
Collaboration and Transition
- Distributing AI-created stories to developers
- Maintaining traceability from features to test cases
- Drafting documentation for stakeholder approval
Recap and Future Steps
Requirements
- Foundational knowledge of software project lifecycles
- Exposure to Agile or Scrum methodologies
- No prior technical expertise necessary
Target 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
