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Duration 7 hours
Course Outline
Introduction to AI in Requirements Engineering
- An overview of AI tools available to product teams
- The role of requirements within Agile and Scrum frameworks
- Advantages and constraints of employing AI for requirement capture
Collecting and Organizing Requirements with AI
- Simulated interviews with AI: converting verbal input into requirements
- Prompting strategies to clarify vague statements
- Structuring requirements into themes and features
Creating User Stories and Epics
- Converting plain text into actionable user stories
- Leveraging AI to identify actors, actions, and objectives
- Developing epics and story hierarchies based on AI suggestions
Drafting Acceptance Criteria and Edge Cases
- Formulating testable Given-When-Then criteria
- Detecting exception paths and boundary conditions with AI assistance
- Evaluating AI-generated outputs for clarity and completeness
Refinement and Story Grooming using AI
- Condensing stakeholder meeting notes and summaries
- Dividing and combining stories using prompt guidance
- Streamlining backlog refinement with AI support
Collaboration and Handover
- Distributing AI-generated stories to developers
- Maintaining traceability from features to test cases
- Preparing documentation for stakeholder approval
Conclusion and Next Steps
Requirements
- Fundamental knowledge of software project lifecycles
- Experience with Agile or Scrum frameworks
- 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
