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Duration 7 hours
Course Outline
Intro to AI in Requirements Engineering
- Overview of AI tools beneficial for product teams
- The role of requirements within Agile and Scrum methodologies
- Advantages and constraints of AI in requirement capture
Collecting and Structuring Requirements via AI
- AI-assisted interview simulations: converting spoken input into requirements
- Prompt engineering techniques to clarify ambiguous statements
- Categorizing requirements into thematic features
Creating User Stories and Epics
- Translating plain text into actionable user stories
- Identifying actors, actions, and goals with AI assistance
- Building epics and story hierarchies based on AI suggestions
Drafting Acceptance Criteria and Edge Cases
- Generating testable Given-When-Then criteria
- Detecting exception paths and boundary conditions using AI
- Reviewing AI-generated outputs for clarity and completeness
Refining and Grooming Stories with AI
- Summarizing stakeholder meetings and notes efficiently
- Splitting and merging stories using prompt-based guidance
- Streamlining backlog refinement with AI support
Team Collaboration and Handoffs
- Sharing AI-generated stories with development teams
- Maintaining traceability from features to test cases
- Creating documentation for stakeholder approval
Wrap-up and Future Steps
Requirements
- Foundational knowledge of software project lifecycles.
- Basic familiarity with Agile or Scrum frameworks.
- No prior technical coding 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
