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Duration 7 hours
Course Outline
Introduction to AI in Requirements Engineering
- Overview of AI tools beneficial for product teams
- The significance of requirements within Agile and Scrum frameworks
- Advantages and constraints of AI-assisted requirement capture
Collecting and Structuring Requirements via AI
- Simulating interviews with AI to convert verbal inputs into requirements
- Prompting strategies to resolve ambiguous statements
- Categorizing requirements into distinct themes and features
Creating User Stories and Epics
- Converting plain text into executable user stories
- Identifying actors, actions, and objectives using AI
- Building epics and story hierarchies based on AI recommendations
Drafting Acceptance Criteria and Edge Cases
- Producing testable Given-When-Then criteria
- Detecting exception paths and boundary conditions with AI assistance
- Evaluating AI outputs for clarity and completeness
Refinement and Story Grooming with AI
- Summarizing stakeholder meetings and notes
- Splitting and merging stories guided by prompts
- Streamlining backlog refinement with AI support
Collaboration and Handoff
- Distributing AI-generated stories to developers
- Maintaining traceability from feature implementation to test cases
- Preparing documentation for stakeholder approval
Conclusion and Future Steps
Requirements
- Fundamental knowledge of software project lifecycles.
- Familiarity with Agile or Scrum methodologies.
- 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
