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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 role of requirements within Agile and Scrum frameworks
- Assessing the benefits and constraints of AI in requirement capture
Collecting and Structuring Requirements with AI
- Simulating interviews with AI to convert verbal feedback into requirements
- Applying prompting techniques to clarify ambiguous statements
- Categorising requirements into themes and features
Creating User Stories and Epics
- Transforming plain text into actionable user stories
- Utilising AI to identify actors, actions, and objectives
- Developing epics and story hierarchies based on AI suggestions
Drafting Acceptance Criteria and Edge Cases
- Generating testable Given-When-Then criteria
- Identifying exception paths and boundary conditions using AI
- Reviewing AI outputs for clarity and thoroughness
Refinement and Story Grooming with AI
- Summarising notes from stakeholder meetings
- Splitting and merging stories guided by AI prompts
- Automating backlog refinement with AI support
Collaboration and Handover
- Distributing AI-generated stories to development teams
- Maintaining traceability from features to test cases
- Producing documentation for stakeholder approval
Conclusion and Next Steps
Requirements
- Fundamental knowledge 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
