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Duration 7 hours
Course Outline
Introduction to AI in Requirements Engineering
- Survey of AI tools suitable for product teams.
- The pivotal role of requirements within Agile and Scrum frameworks.
- Advantages and constraints of utilising AI for requirement capture.
Capturing and Structuring Requirements with AI
- Simulated interviews with AI: translating verbal input into formal requirements.
- Prompting strategies to clarify ambiguous descriptions.
- Categorising requirements into distinct themes and features.
Creating User Stories and Epics
- Converting unstructured text into actionable user stories.
- Utilising AI to identify key actors, actions, and objectives.
- Building epics and hierarchical story structures based on AI insights.
Defining Acceptance Criteria and Edge Cases
- Formulating testable criteria using Given-When-Then formats.
- Pinpointing exception paths and boundary conditions with AI aid.
- Evaluating AI-generated outputs for clarity and thoroughness.
Refinement and Story Grooming with AI
- Synthesising notes and outcomes from stakeholder meetings.
- Segmenting and consolidating stories with guided prompting.
- Streamlining backlog refinement processes with AI support.
Collaboration and Handover
- Distributing AI-assisted stories to development teams.
- Maintaining traceability from initial features through to test cases.
- Producing documentation for stakeholder approval.
Conclusion and Future Directions
Requirements
- Foundational knowledge of software project lifecycles.
- Familiarity with Agile or Scrum methodologies.
- No prior technical experience 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
