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Duration 7 hours
Course Outline
Introduction to AI in Requirements Engineering
- Overview of AI tools for product teams
- Understanding the significance of requirements in Agile and Scrum
- Advantages and constraints of using AI for capturing requirements
Collecting and Structuring Requirements with AI
- AI-powered interview simulations: converting verbal input into requirements
- Prompting methods to clarify ambiguous statements
- Categorizing requirements into themes and features
Creating User Stories and Epics
- Converting plain text into executable user stories
- Leveraging AI to identify actors, actions, and objectives
- Building epics and story hierarchies based on AI suggestions
Drafting Acceptance Criteria and Edge Cases
- Generating Given-When-Then testable criteria
- Detecting exception paths and boundary conditions with AI
- Evaluating AI outputs for clarity and completeness
Refinement and Story Grooming with AI
- Summarizing stakeholder meetings and notes
- Dividing and merging stories using prompt guidance
- Streamlining backlog refinement with AI support
Collaboration and Handoff
- Distributing AI-generated stories to developers
- Ensuring traceability from features to test cases
- Creating documentation for stakeholder approval
Summary and Next Steps
Requirements
- Fundamental knowledge of software project lifecycles
- Familiarity with Agile or Scrum frameworks
- No 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