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Duration 7 hours
Course Outline
Introduction to AI in Requirements Engineering
- Overview of AI tools relevant to product teams.
- Exploring the significance of requirements within Agile and Scrum contexts.
- Evaluating the advantages and constraints of AI-assisted requirement capture.
Collecting and Structuring Requirements with AI
- Simulating interviews with AI to convert verbal feedback into formal requirements.
- Applying prompting strategies to clarify vague or ambiguous statements.
- Categorizing requirements into distinct themes and features.
Creating User Stories and Epics
- Converting raw text into executable user stories.
- Leveraging AI to pinpoint actors, actions, and objectives.
- Developing epics and story hierarchies based on AI-generated suggestions.
Drafting Acceptance Criteria and Edge Cases
- Producing testable Given-When-Then criteria.
- Detecting exception paths and boundary conditions with AI assistance.
- Assessing AI outputs for clarity and completeness.
Refining and Grooming Stories with AI
- Condensing notes from stakeholder meetings.
- Breaking down or combining stories using guided prompts.
- Streamlining backlog refinement processes with AI support.
Collaboration and Handoff
- Sharing AI-generated stories with development teams.
- Maintaining traceability from initial features to final test cases.
- Preparing documentation for stakeholder approval.
Recap and Future Directions
Requirements
- Foundational knowledge of software project lifecycles.
- Basic familiarity with Agile or Scrum methodologies.
- No prior technical experience 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
