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Duration 7 hours
Course Outline
Introduction to AI for Requirements Engineering
- An overview of AI tools available for product teams
- The role of requirements within Agile and Scrum frameworks
- Advantages and constraints of AI in requirement capture
Gathering and Structuring Requirements with AI
- Simulated AI interviews: converting verbal feedback into formal requirements
- Prompting strategies for clarifying ambiguous statements
- Structuring requirements into coherent themes and features
Generating User Stories and Epics
- Converting plain text inputs into actionable user stories
- Leveraging AI to identify key actors, actions, and goals
- Developing epics and story hierarchies based on AI suggestions
Writing Acceptance Criteria and Edge Cases
- Creating testable Given-When-Then criteria
- Using AI to spot exception paths and boundary conditions
- Evaluating AI-generated outputs for clarity and completeness
Refinement and Story Grooming with AI
- Summarizing key points from stakeholder meetings and notes
- Splitting or merging stories guided by prompts
- Streamlining backlog refinement with AI assistance
Collaboration and Handoff
- Sharing AI-generated stories with development teams
- Maintaining traceability from features to test cases
- Producing documentation for final stakeholder approval
Summary and Next Steps
Requirements
- A foundational understanding of software project lifecycles
- Familiarity 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