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Duration 7 hours
Course Outline
Introduction to AI in Requirements Engineering
- Overview of AI tools available to product teams
- The significance of requirements within Agile and Scrum methodologies
- The advantages and constraints of employing AI for capturing requirements
Collecting and Organizing Requirements via AI
- Simulating interviews with AI to convert verbal input into formal requirements
- Prompting strategies to resolve ambiguous statements
- Structuring requirements into distinct themes and features
Creating User Stories and Epics
- Converting plain text into actionable user stories
- Utilizing AI to pinpoint actors, actions, and objectives
- Building epics and story hierarchies based on AI suggestions
Drafting Acceptance Criteria and Edge Cases
- Producing testable criteria using the Given-When-Then format
- Detecting exception paths and boundary conditions with AI assistance
- Evaluating AI outputs for clarity and completeness
Refining and Grooming Stories with AI
- Condensing notes and summaries from stakeholder meetings
- Splitting and merging stories guided by prompts
- Streamlining backlog refinement through AI support
Collaboration and Handover
- Distributing AI-generated stories to developers
- Maintaining traceability from features to test cases
- Creating documentation for stakeholder approval
Conclusion and Future Steps
Requirements
- Foundational knowledge of software project lifecycles
- Familiarity with Agile or Scrum frameworks
- No prior technical expertise 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
