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Course Outline
Introduction to AI for Requirements Engineering
- Overview of AI tools available for product teams
- Understanding the role of requirements in Agile and Scrum
- Benefits and limitations of using AI for requirement capture
Gathering and Structuring Requirements with AI
- Simulating interviews with AI: converting verbal input into requirements
- Prompting techniques to clarify ambiguous statements
- Organizing requirements into themes and features
Generating User Stories and Epics
- Converting plain text into actionable user stories
- Using AI to identify actors, actions, and goals
- Creating epics and story hierarchies based on AI suggestions
Writing Acceptance Criteria and Edge Cases
- Generating testable criteria using the Given-When-Then format
- Identifying exception paths and boundary conditions with AI
- Reviewing AI outputs for clarity and completeness
Refinement and Story Grooming with AI
- Summarizing stakeholder meetings and notes
- Splitting and merging stories using prompt guidance
- Automating backlog refinement with AI assistance
Collaboration and Handoff
- Sharing AI-generated stories with developers
- Ensuring traceability from feature to test case
- Generating documentation for stakeholder sign-off
Summary and Next Steps
Requirements
- Foundational knowledge of software project lifecycles
- Familiarity with Agile or Scrum frameworks
- No prior technical background required
Target Audience
- Product Owners
- Business Analysts
- Scrum Masters
7 Hours
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
