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Duration 7 hours
Course Outline
Introduction to AI in Requirements Engineering
- Overview of AI tools relevant to product teams
- The significance of requirements within Agile and Scrum frameworks
- Advantages and constraints of utilizing AI for requirement capture
Collecting and Structuring Requirements with AI
- AI-powered interview simulations: converting verbal feedback into requirements
- Prompting strategies to resolve ambiguous statements
- Grouping requirements into coherent themes and features
Creating User Stories and Epics
- Converting plain text into actionable user stories
- Employing AI to pinpoint actors, actions, and objectives
- Building epics and story hierarchies based on AI insights
Drafting Acceptance Criteria and Edge Cases
- Producing testable criteria in Given-When-Then format
- Identifying exception paths and boundary conditions with AI assistance
- Evaluating AI-generated outputs for clarity and completeness
Refining and Grooming Stories with AI
- Summarizing stakeholder meetings and notes efficiently
- Using prompt guidance to split or merge stories
- Streamlining backlog refinement with AI support
Collaboration and Handoff
- Sharing AI-generated stories with development teams
- Maintaining traceability from features to test cases
- Preparing documentation for stakeholder approval
Conclusion and Future Steps
Requirements
- Foundational knowledge of software project lifecycles
- Familiarity with Agile or Scrum methodologies
- No prior technical background is 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
