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Duration 7 hours
Course Outline
Introduction to AI in Requirements Engineering
- An overview of AI tools available to product teams
- Exploring the significance of requirements within Agile and Scrum
- The advantages and constraints of applying AI to requirement capture
Collecting and Structuring Requirements via AI
- Simulating interviews with AI to convert spoken input into requirements
- Utilizing prompting methods to resolve ambiguous statements
- Grouping requirements into themes and features
Creating User Stories and Epics
- Converting plain text into actionable user stories
- Leveraging AI to pinpoint actors, actions, and objectives
- Building epics and story hierarchies based on AI suggestions
Drafting Acceptance Criteria and Edge Cases
- Generating testable criteria using Given-When-Then formats
- Detecting exception paths and boundary conditions with AI support
- Evaluating AI outputs for clarity and thoroughness
Refinement and Story Grooming Assisted by AI
- Summarizing discussions and notes from stakeholder meetings
- Dividing and consolidating stories through guided prompting
- Streamlining backlog refinement with AI assistance
Collaboration and Transition
- Sharing AI-generated stories with development teams
- Maintaining traceability from features to test cases
- Producing documentation for stakeholder approval
Conclusion and Future Steps
Requirements
- Fundamental knowledge of software project lifecycles
- Experience 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