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Course Outline
Introduction to AI in Requirements Engineering
- Overview of AI tools available for product teams.
- Understanding the role of requirements in Agile and Scrum contexts.
- Exploring the benefits and limitations of using AI for requirement capture.
Gathering and Structuring Requirements with AI
- Simulating interviews with AI to convert verbal input into written requirements.
- Applying prompting techniques to clarify ambiguous statements.
- Organizing requirements into coherent themes and features.
Generating User Stories and Epics
- Converting plain text into actionable user stories.
- Using AI to identify actors, actions, and goals.
- Constructing epics and story hierarchies based on AI suggestions.
Writing Acceptance Criteria and Identifying Edge Cases
- Generating testable criteria using the Given-When-Then format.
- Identifying exception paths and boundary conditions with AI assistance.
- Reviewing AI-generated outputs for clarity and completeness.
Refinement and Story Grooming with AI
- Summarizing stakeholder meetings and notes.
- Splitting and merging stories using guided prompts.
- Automating backlog refinement processes with AI support.
Collaboration and Handoff
- Sharing AI-generated stories with development teams.
- Ensuring traceability from features to test cases.
- Generating documentation for stakeholder sign-off.
Summary and Next Steps
Requirements
- Fundamental knowledge of software project lifecycles.
- Familiarity with Agile or Scrum frameworks.
- No technical background is required.
Target Audience
- Product Owners
- Business Analysts
- Scrum Masters
7 Hours
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
